Build: Bump huggingface-hub from 1.24.0 to 1.28.0

[dependabot]

Bumps huggingface-hub from 1.24.0 to 1.28.0.

Release notes

Sourced from huggingface-hub's releases.

[v1.28.0] Hardware discovery and managed engine images for Inference Endpoints and more

🔎 Discover deployable hardware with hf endpoints hardware

Deploying an Inference Endpoint requires five hardware flags (--vendor, --region, --accelerator, --instance-type, --instance-size) whose valid values depend on each other, and until now there was no way to learn them from the CLI. The new hf endpoints hardware command lists the valid combinations along with the price per replica per hour and your namespace's accelerator quota, filtered by default to the hardware you can deploy on right now. The same data is available in the SDK via list_inference_endpoints_hardware(), which flattens the API response into InferenceEndpointHardware objects you can filter programmatically.

>>> hf endpoints hardware --vendor aws --region eu-west-1
VENDOR REGION ACCELERATOR INSTANCE_TYPE INSTANCE_SIZE MEMORY_GB GPU_MEMORY_GB PRICE_PER_HOUR QUOTA STATUS
------ --------- ----------- ------------- ------------- --------- ------------- -------------- ----- ---------
aws eu-west-1 cpu intel-spr x1 2.0 0.033 0/60 available
aws eu-west-1 cpu intel-spr x2 4.0 0.067 0/60 available
aws eu-west-1 gpu nvidia-a10g x1 30.0 24 1.0 0/16 available
aws eu-west-1 gpu nvidia-t4 x1 15.0 16 0.5 1/30 available

• [Inference Endpoints] Add hf endpoints hardware to list available instances by @​hanouticelina in #4672

🚀 Managed engine images and multi-accelerator parallelism for Inference Endpoints

custom_image now accepts the engine-specific container types supported by the API: key the dictionary with the engine name (vLLM, sGLang, tgi, tei, llamacpp, hfServe, ...) instead of leaving it flat, and each engine takes the usual container fields plus its own tuning options. Any dict without a top-level url is forwarded to the API untouched, so engines added to the API later will work without upgrading huggingface_hub, and update_inference_endpoint now handles the same payload shapes as create_inference_endpoint. On the CLI, hf endpoints deploy and hf endpoints update gain --engine, --tensor-parallel-size and --data-parallel-size, and update also accepts --custom-image, --health-route and --port. This matters because vLLM and SGLang default to a single accelerator while an endpoint is allocated every accelerator of its instance — the API now rejects that misconfiguration, and these flags are how you set things right.

$ hf endpoints deploy gpt-oss-120b-vllm --repo openai/gpt-oss-120b --framework custom \
--accelerator gpu --instance-size x8 --instance-type nvidia-h200 --region us-east-1 --vendor aws \
--engine vllm --custom-image vllm/vllm-openai:v0.23.0 --tensor-parallel-size 8
Retune a running endpoint
$ hf endpoints update gpt-oss-120b-vllm --tensor-parallel-size 4 --data-parallel-size 2

💔 Breaking change:huggingface_hub.constants.INFERENCE_ENDPOINT_IMAGE_KEYS is removed. It was never exported at the package root nor documented, but code reading it directly will now get an AttributeError.

• [Inference Endpoints] Support managed engine images in custom_image by @​hanouticelina in #4671
• [CLI] Add --tensor-parallel-size / --data-parallel-size to hf endpoints deploy and update by @​moon-bot-app[bot] in #4661

🤖 Inference

• [Inference Providers] deepinfra: add text-to-speech support by @​ovuruska in #4559
• [Inference Providers] deepinfra: add feature-extraction support by @​ovuruska in #4656

🖥️ CLI

• [CLI] Keep hf extensions off the metered GitHub REST API by @​hanouticelina in #4659

🐛 Bug and typo fixes

• [CLI] Fix scheduled upload of a single file in a subfolder by @​dfedoryshchev in #4619
• [Download] Fix tqdm_class ignored by the Xet transfer bar by @​bharadwaj-pendyala in #4647

... (truncated)

Commits

• b2da2d4 Release: v1.28.0
• a718e44 Release: v1.28.0.rc0
• 7105c3d [CLI] Add --tensor-parallel-size / --data-parallel-size to `hf endpoints depl...
• a3d9d8a [Inference Endpoints] Omit model.task instead of sending null on create (#4...
• 909b162 [Inference Endpoints] Add hf endpoints hardware to list available instances...
• 5ac9711 Do not use a redirect's Content-Length as file size in get_hf_file_metadata (...
• 99aba55 [Docs] Normalize malformed docstring parameter entries (#4623)
• 2e6c67d [Inference Providers] deepinfra: add feature-extraction (embeddings) support ...
• 7a522f0 docs: remove obsolete Repository guide references (#4679)
• aa40a65 [Download] Fix ResolvedRevision string value after pickle/copy (#4692)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

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[dependabot]

Bumps huggingface-hub from 1.24.0 to 1.28.0.

Release notes

Sourced from huggingface-hub's releases.

[v1.28.0] Hardware discovery and managed engine images for Inference Endpoints and more

🔎 Discover deployable hardware with hf endpoints hardware

Deploying an Inference Endpoint requires five hardware flags (--vendor, --region, --accelerator, --instance-type, --instance-size) whose valid values depend on each other, and until now there was no way to learn them from the CLI. The new hf endpoints hardware command lists the valid combinations along with the price per replica per hour and your namespace's accelerator quota, filtered by default to the hardware you can deploy on right now. The same data is available in the SDK via list_inference_endpoints_hardware(), which flattens the API response into InferenceEndpointHardware objects you can filter programmatically.

>>> hf endpoints hardware --vendor aws --region eu-west-1
VENDOR REGION ACCELERATOR INSTANCE_TYPE INSTANCE_SIZE MEMORY_GB GPU_MEMORY_GB PRICE_PER_HOUR QUOTA STATUS
------ --------- ----------- ------------- ------------- --------- ------------- -------------- ----- ---------
aws eu-west-1 cpu intel-spr x1 2.0 0.033 0/60 available
aws eu-west-1 cpu intel-spr x2 4.0 0.067 0/60 available
aws eu-west-1 gpu nvidia-a10g x1 30.0 24 1.0 0/16 available
aws eu-west-1 gpu nvidia-t4 x1 15.0 16 0.5 1/30 available

• [Inference Endpoints] Add hf endpoints hardware to list available instances by @​hanouticelina in #4672

🚀 Managed engine images and multi-accelerator parallelism for Inference Endpoints

custom_image now accepts the engine-specific container types supported by the API: key the dictionary with the engine name (vLLM, sGLang, tgi, tei, llamacpp, hfServe, ...) instead of leaving it flat, and each engine takes the usual container fields plus its own tuning options. Any dict without a top-level url is forwarded to the API untouched, so engines added to the API later will work without upgrading huggingface_hub, and update_inference_endpoint now handles the same payload shapes as create_inference_endpoint. On the CLI, hf endpoints deploy and hf endpoints update gain --engine, --tensor-parallel-size and --data-parallel-size, and update also accepts --custom-image, --health-route and --port. This matters because vLLM and SGLang default to a single accelerator while an endpoint is allocated every accelerator of its instance — the API now rejects that misconfiguration, and these flags are how you set things right.

$ hf endpoints deploy gpt-oss-120b-vllm --repo openai/gpt-oss-120b --framework custom \
--accelerator gpu --instance-size x8 --instance-type nvidia-h200 --region us-east-1 --vendor aws \
--engine vllm --custom-image vllm/vllm-openai:v0.23.0 --tensor-parallel-size 8
Retune a running endpoint
$ hf endpoints update gpt-oss-120b-vllm --tensor-parallel-size 4 --data-parallel-size 2

💔 Breaking change:huggingface_hub.constants.INFERENCE_ENDPOINT_IMAGE_KEYS is removed. It was never exported at the package root nor documented, but code reading it directly will now get an AttributeError.

• [Inference Endpoints] Support managed engine images in custom_image by @​hanouticelina in #4671
• [CLI] Add --tensor-parallel-size / --data-parallel-size to hf endpoints deploy and update by @​moon-bot-app[bot] in #4661

🤖 Inference

• [Inference Providers] deepinfra: add text-to-speech support by @​ovuruska in #4559
• [Inference Providers] deepinfra: add feature-extraction support by @​ovuruska in #4656

🖥️ CLI

• [CLI] Keep hf extensions off the metered GitHub REST API by @​hanouticelina in #4659

🐛 Bug and typo fixes

• [CLI] Fix scheduled upload of a single file in a subfolder by @​dfedoryshchev in #4619
• [Download] Fix tqdm_class ignored by the Xet transfer bar by @​bharadwaj-pendyala in #4647

... (truncated)

Commits

• b2da2d4 Release: v1.28.0
• a718e44 Release: v1.28.0.rc0
• 7105c3d [CLI] Add --tensor-parallel-size / --data-parallel-size to `hf endpoints depl...
• a3d9d8a [Inference Endpoints] Omit model.task instead of sending null on create (#4...
• 909b162 [Inference Endpoints] Add hf endpoints hardware to list available instances...
• 5ac9711 Do not use a redirect's Content-Length as file size in get_hf_file_metadata (...
• 99aba55 [Docs] Normalize malformed docstring parameter entries (#4623)
• 2e6c67d [Inference Providers] deepinfra: add feature-extraction (embeddings) support ...
• 7a522f0 docs: remove obsolete Repository guide references (#4679)
• aa40a65 [Download] Fix ResolvedRevision string value after pickle/copy (#4692)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

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• @dependabot rebase will rebase this PR
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[dependabot]

Bumps huggingface-hub from 1.24.0 to 1.28.0.

Release notes

Sourced from huggingface-hub's releases.

[v1.28.0] Hardware discovery and managed engine images for Inference Endpoints and more

🔎 Discover deployable hardware with hf endpoints hardware

Deploying an Inference Endpoint requires five hardware flags (--vendor, --region, --accelerator, --instance-type, --instance-size) whose valid values depend on each other, and until now there was no way to learn them from the CLI. The new hf endpoints hardware command lists the valid combinations along with the price per replica per hour and your namespace's accelerator quota, filtered by default to the hardware you can deploy on right now. The same data is available in the SDK via list_inference_endpoints_hardware(), which flattens the API response into InferenceEndpointHardware objects you can filter programmatically.

>>> hf endpoints hardware --vendor aws --region eu-west-1
VENDOR REGION ACCELERATOR INSTANCE_TYPE INSTANCE_SIZE MEMORY_GB GPU_MEMORY_GB PRICE_PER_HOUR QUOTA STATUS
------ --------- ----------- ------------- ------------- --------- ------------- -------------- ----- ---------
aws eu-west-1 cpu intel-spr x1 2.0 0.033 0/60 available
aws eu-west-1 cpu intel-spr x2 4.0 0.067 0/60 available
aws eu-west-1 gpu nvidia-a10g x1 30.0 24 1.0 0/16 available
aws eu-west-1 gpu nvidia-t4 x1 15.0 16 0.5 1/30 available

• [Inference Endpoints] Add hf endpoints hardware to list available instances by @​hanouticelina in #4672

🚀 Managed engine images and multi-accelerator parallelism for Inference Endpoints

custom_image now accepts the engine-specific container types supported by the API: key the dictionary with the engine name (vLLM, sGLang, tgi, tei, llamacpp, hfServe, ...) instead of leaving it flat, and each engine takes the usual container fields plus its own tuning options. Any dict without a top-level url is forwarded to the API untouched, so engines added to the API later will work without upgrading huggingface_hub, and update_inference_endpoint now handles the same payload shapes as create_inference_endpoint. On the CLI, hf endpoints deploy and hf endpoints update gain --engine, --tensor-parallel-size and --data-parallel-size, and update also accepts --custom-image, --health-route and --port. This matters because vLLM and SGLang default to a single accelerator while an endpoint is allocated every accelerator of its instance — the API now rejects that misconfiguration, and these flags are how you set things right.

$ hf endpoints deploy gpt-oss-120b-vllm --repo openai/gpt-oss-120b --framework custom \
--accelerator gpu --instance-size x8 --instance-type nvidia-h200 --region us-east-1 --vendor aws \
--engine vllm --custom-image vllm/vllm-openai:v0.23.0 --tensor-parallel-size 8
Retune a running endpoint
$ hf endpoints update gpt-oss-120b-vllm --tensor-parallel-size 4 --data-parallel-size 2

💔 Breaking change:huggingface_hub.constants.INFERENCE_ENDPOINT_IMAGE_KEYS is removed. It was never exported at the package root nor documented, but code reading it directly will now get an AttributeError.

• [Inference Endpoints] Support managed engine images in custom_image by @​hanouticelina in #4671
• [CLI] Add --tensor-parallel-size / --data-parallel-size to hf endpoints deploy and update by @​moon-bot-app[bot] in #4661

🤖 Inference

• [Inference Providers] deepinfra: add text-to-speech support by @​ovuruska in #4559
• [Inference Providers] deepinfra: add feature-extraction support by @​ovuruska in #4656

🖥️ CLI

• [CLI] Keep hf extensions off the metered GitHub REST API by @​hanouticelina in #4659

🐛 Bug and typo fixes

• [CLI] Fix scheduled upload of a single file in a subfolder by @​dfedoryshchev in #4619
• [Download] Fix tqdm_class ignored by the Xet transfer bar by @​bharadwaj-pendyala in #4647

... (truncated)

Commits

• b2da2d4 Release: v1.28.0
• a718e44 Release: v1.28.0.rc0
• 7105c3d [CLI] Add --tensor-parallel-size / --data-parallel-size to `hf endpoints depl...
• a3d9d8a [Inference Endpoints] Omit model.task instead of sending null on create (#4...
• 909b162 [Inference Endpoints] Add hf endpoints hardware to list available instances...
• 5ac9711 Do not use a redirect's Content-Length as file size in get_hf_file_metadata (...
• 99aba55 [Docs] Normalize malformed docstring parameter entries (#4623)
• 2e6c67d [Inference Providers] deepinfra: add feature-extraction (embeddings) support ...
• 7a522f0 docs: remove obsolete Repository guide references (#4679)
• aa40a65 [Download] Fix ResolvedRevision string value after pickle/copy (#4692)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

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You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[dependabot]

Bumps huggingface-hub from 1.24.0 to 1.28.0.

Release notes

Sourced from huggingface-hub's releases.

[v1.28.0] Hardware discovery and managed engine images for Inference Endpoints and more

🔎 Discover deployable hardware with hf endpoints hardware

Deploying an Inference Endpoint requires five hardware flags (--vendor, --region, --accelerator, --instance-type, --instance-size) whose valid values depend on each other, and until now there was no way to learn them from the CLI. The new hf endpoints hardware command lists the valid combinations along with the price per replica per hour and your namespace's accelerator quota, filtered by default to the hardware you can deploy on right now. The same data is available in the SDK via list_inference_endpoints_hardware(), which flattens the API response into InferenceEndpointHardware objects you can filter programmatically.

>>> hf endpoints hardware --vendor aws --region eu-west-1
VENDOR REGION ACCELERATOR INSTANCE_TYPE INSTANCE_SIZE MEMORY_GB GPU_MEMORY_GB PRICE_PER_HOUR QUOTA STATUS
------ --------- ----------- ------------- ------------- --------- ------------- -------------- ----- ---------
aws eu-west-1 cpu intel-spr x1 2.0 0.033 0/60 available
aws eu-west-1 cpu intel-spr x2 4.0 0.067 0/60 available
aws eu-west-1 gpu nvidia-a10g x1 30.0 24 1.0 0/16 available
aws eu-west-1 gpu nvidia-t4 x1 15.0 16 0.5 1/30 available

• [Inference Endpoints] Add hf endpoints hardware to list available instances by @​hanouticelina in #4672

🚀 Managed engine images and multi-accelerator parallelism for Inference Endpoints

custom_image now accepts the engine-specific container types supported by the API: key the dictionary with the engine name (vLLM, sGLang, tgi, tei, llamacpp, hfServe, ...) instead of leaving it flat, and each engine takes the usual container fields plus its own tuning options. Any dict without a top-level url is forwarded to the API untouched, so engines added to the API later will work without upgrading huggingface_hub, and update_inference_endpoint now handles the same payload shapes as create_inference_endpoint. On the CLI, hf endpoints deploy and hf endpoints update gain --engine, --tensor-parallel-size and --data-parallel-size, and update also accepts --custom-image, --health-route and --port. This matters because vLLM and SGLang default to a single accelerator while an endpoint is allocated every accelerator of its instance — the API now rejects that misconfiguration, and these flags are how you set things right.

$ hf endpoints deploy gpt-oss-120b-vllm --repo openai/gpt-oss-120b --framework custom \
--accelerator gpu --instance-size x8 --instance-type nvidia-h200 --region us-east-1 --vendor aws \
--engine vllm --custom-image vllm/vllm-openai:v0.23.0 --tensor-parallel-size 8
Retune a running endpoint
$ hf endpoints update gpt-oss-120b-vllm --tensor-parallel-size 4 --data-parallel-size 2

💔 Breaking change:huggingface_hub.constants.INFERENCE_ENDPOINT_IMAGE_KEYS is removed. It was never exported at the package root nor documented, but code reading it directly will now get an AttributeError.

• [Inference Endpoints] Support managed engine images in custom_image by @​hanouticelina in #4671
• [CLI] Add --tensor-parallel-size / --data-parallel-size to hf endpoints deploy and update by @​moon-bot-app[bot] in #4661

🤖 Inference

• [Inference Providers] deepinfra: add text-to-speech support by @​ovuruska in #4559
• [Inference Providers] deepinfra: add feature-extraction support by @​ovuruska in #4656

🖥️ CLI

• [CLI] Keep hf extensions off the metered GitHub REST API by @​hanouticelina in #4659

🐛 Bug and typo fixes

• [CLI] Fix scheduled upload of a single file in a subfolder by @​dfedoryshchev in #4619
• [Download] Fix tqdm_class ignored by the Xet transfer bar by @​bharadwaj-pendyala in #4647

... (truncated)

Commits

• b2da2d4 Release: v1.28.0
• a718e44 Release: v1.28.0.rc0
• 7105c3d [CLI] Add --tensor-parallel-size / --data-parallel-size to `hf endpoints depl...
• a3d9d8a [Inference Endpoints] Omit model.task instead of sending null on create (#4...
• 909b162 [Inference Endpoints] Add hf endpoints hardware to list available instances...
• 5ac9711 Do not use a redirect's Content-Length as file size in get_hf_file_metadata (...
• 99aba55 [Docs] Normalize malformed docstring parameter entries (#4623)
• 2e6c67d [Inference Providers] deepinfra: add feature-extraction (embeddings) support ...
• 7a522f0 docs: remove obsolete Repository guide references (#4679)
• aa40a65 [Download] Fix ResolvedRevision string value after pickle/copy (#4692)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

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You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[dependabot]

Bumps huggingface-hub from 1.24.0 to 1.28.0.

Release notes

Sourced from huggingface-hub's releases.

[v1.28.0] Hardware discovery and managed engine images for Inference Endpoints and more

🔎 Discover deployable hardware with hf endpoints hardware

Deploying an Inference Endpoint requires five hardware flags (--vendor, --region, --accelerator, --instance-type, --instance-size) whose valid values depend on each other, and until now there was no way to learn them from the CLI. The new hf endpoints hardware command lists the valid combinations along with the price per replica per hour and your namespace's accelerator quota, filtered by default to the hardware you can deploy on right now. The same data is available in the SDK via list_inference_endpoints_hardware(), which flattens the API response into InferenceEndpointHardware objects you can filter programmatically.

>>> hf endpoints hardware --vendor aws --region eu-west-1
VENDOR REGION ACCELERATOR INSTANCE_TYPE INSTANCE_SIZE MEMORY_GB GPU_MEMORY_GB PRICE_PER_HOUR QUOTA STATUS
------ --------- ----------- ------------- ------------- --------- ------------- -------------- ----- ---------
aws eu-west-1 cpu intel-spr x1 2.0 0.033 0/60 available
aws eu-west-1 cpu intel-spr x2 4.0 0.067 0/60 available
aws eu-west-1 gpu nvidia-a10g x1 30.0 24 1.0 0/16 available
aws eu-west-1 gpu nvidia-t4 x1 15.0 16 0.5 1/30 available

• [Inference Endpoints] Add hf endpoints hardware to list available instances by @​hanouticelina in #4672

🚀 Managed engine images and multi-accelerator parallelism for Inference Endpoints

custom_image now accepts the engine-specific container types supported by the API: key the dictionary with the engine name (vLLM, sGLang, tgi, tei, llamacpp, hfServe, ...) instead of leaving it flat, and each engine takes the usual container fields plus its own tuning options. Any dict without a top-level url is forwarded to the API untouched, so engines added to the API later will work without upgrading huggingface_hub, and update_inference_endpoint now handles the same payload shapes as create_inference_endpoint. On the CLI, hf endpoints deploy and hf endpoints update gain --engine, --tensor-parallel-size and --data-parallel-size, and update also accepts --custom-image, --health-route and --port. This matters because vLLM and SGLang default to a single accelerator while an endpoint is allocated every accelerator of its instance — the API now rejects that misconfiguration, and these flags are how you set things right.

$ hf endpoints deploy gpt-oss-120b-vllm --repo openai/gpt-oss-120b --framework custom \
--accelerator gpu --instance-size x8 --instance-type nvidia-h200 --region us-east-1 --vendor aws \
--engine vllm --custom-image vllm/vllm-openai:v0.23.0 --tensor-parallel-size 8
Retune a running endpoint
$ hf endpoints update gpt-oss-120b-vllm --tensor-parallel-size 4 --data-parallel-size 2

💔 Breaking change:huggingface_hub.constants.INFERENCE_ENDPOINT_IMAGE_KEYS is removed. It was never exported at the package root nor documented, but code reading it directly will now get an AttributeError.

• [Inference Endpoints] Support managed engine images in custom_image by @​hanouticelina in #4671
• [CLI] Add --tensor-parallel-size / --data-parallel-size to hf endpoints deploy and update by @​moon-bot-app[bot] in #4661

🤖 Inference

• [Inference Providers] deepinfra: add text-to-speech support by @​ovuruska in #4559
• [Inference Providers] deepinfra: add feature-extraction support by @​ovuruska in #4656

🖥️ CLI

• [CLI] Keep hf extensions off the metered GitHub REST API by @​hanouticelina in #4659

🐛 Bug and typo fixes

• [CLI] Fix scheduled upload of a single file in a subfolder by @​dfedoryshchev in #4619
• [Download] Fix tqdm_class ignored by the Xet transfer bar by @​bharadwaj-pendyala in #4647

... (truncated)

Commits

• b2da2d4 Release: v1.28.0
• a718e44 Release: v1.28.0.rc0
• 7105c3d [CLI] Add --tensor-parallel-size / --data-parallel-size to `hf endpoints depl...
• a3d9d8a [Inference Endpoints] Omit model.task instead of sending null on create (#4...
• 909b162 [Inference Endpoints] Add hf endpoints hardware to list available instances...
• 5ac9711 Do not use a redirect's Content-Length as file size in get_hf_file_metadata (...
• 99aba55 [Docs] Normalize malformed docstring parameter entries (#4623)
• 2e6c67d [Inference Providers] deepinfra: add feature-extraction (embeddings) support ...
• 7a522f0 docs: remove obsolete Repository guide references (#4679)
• aa40a65 [Download] Fix ResolvedRevision string value after pickle/copy (#4692)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

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You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[dependabot]

Bumps huggingface-hub from 1.24.0 to 1.28.0.

Release notes

Sourced from huggingface-hub's releases.

[v1.28.0] Hardware discovery and managed engine images for Inference Endpoints and more

🔎 Discover deployable hardware with hf endpoints hardware

Deploying an Inference Endpoint requires five hardware flags (--vendor, --region, --accelerator, --instance-type, --instance-size) whose valid values depend on each other, and until now there was no way to learn them from the CLI. The new hf endpoints hardware command lists the valid combinations along with the price per replica per hour and your namespace's accelerator quota, filtered by default to the hardware you can deploy on right now. The same data is available in the SDK via list_inference_endpoints_hardware(), which flattens the API response into InferenceEndpointHardware objects you can filter programmatically.

>>> hf endpoints hardware --vendor aws --region eu-west-1
VENDOR REGION ACCELERATOR INSTANCE_TYPE INSTANCE_SIZE MEMORY_GB GPU_MEMORY_GB PRICE_PER_HOUR QUOTA STATUS
------ --------- ----------- ------------- ------------- --------- ------------- -------------- ----- ---------
aws eu-west-1 cpu intel-spr x1 2.0 0.033 0/60 available
aws eu-west-1 cpu intel-spr x2 4.0 0.067 0/60 available
aws eu-west-1 gpu nvidia-a10g x1 30.0 24 1.0 0/16 available
aws eu-west-1 gpu nvidia-t4 x1 15.0 16 0.5 1/30 available

• [Inference Endpoints] Add hf endpoints hardware to list available instances by @​hanouticelina in #4672

🚀 Managed engine images and multi-accelerator parallelism for Inference Endpoints

custom_image now accepts the engine-specific container types supported by the API: key the dictionary with the engine name (vLLM, sGLang, tgi, tei, llamacpp, hfServe, ...) instead of leaving it flat, and each engine takes the usual container fields plus its own tuning options. Any dict without a top-level url is forwarded to the API untouched, so engines added to the API later will work without upgrading huggingface_hub, and update_inference_endpoint now handles the same payload shapes as create_inference_endpoint. On the CLI, hf endpoints deploy and hf endpoints update gain --engine, --tensor-parallel-size and --data-parallel-size, and update also accepts --custom-image, --health-route and --port. This matters because vLLM and SGLang default to a single accelerator while an endpoint is allocated every accelerator of its instance — the API now rejects that misconfiguration, and these flags are how you set things right.

$ hf endpoints deploy gpt-oss-120b-vllm --repo openai/gpt-oss-120b --framework custom \
--accelerator gpu --instance-size x8 --instance-type nvidia-h200 --region us-east-1 --vendor aws \
--engine vllm --custom-image vllm/vllm-openai:v0.23.0 --tensor-parallel-size 8
Retune a running endpoint
$ hf endpoints update gpt-oss-120b-vllm --tensor-parallel-size 4 --data-parallel-size 2

💔 Breaking change:huggingface_hub.constants.INFERENCE_ENDPOINT_IMAGE_KEYS is removed. It was never exported at the package root nor documented, but code reading it directly will now get an AttributeError.

• [Inference Endpoints] Support managed engine images in custom_image by @​hanouticelina in #4671
• [CLI] Add --tensor-parallel-size / --data-parallel-size to hf endpoints deploy and update by @​moon-bot-app[bot] in #4661

🤖 Inference

• [Inference Providers] deepinfra: add text-to-speech support by @​ovuruska in #4559
• [Inference Providers] deepinfra: add feature-extraction support by @​ovuruska in #4656

🖥️ CLI

• [CLI] Keep hf extensions off the metered GitHub REST API by @​hanouticelina in #4659

🐛 Bug and typo fixes

• [CLI] Fix scheduled upload of a single file in a subfolder by @​dfedoryshchev in #4619
• [Download] Fix tqdm_class ignored by the Xet transfer bar by @​bharadwaj-pendyala in #4647

... (truncated)

Commits

• b2da2d4 Release: v1.28.0
• a718e44 Release: v1.28.0.rc0
• 7105c3d [CLI] Add --tensor-parallel-size / --data-parallel-size to `hf endpoints depl...
• a3d9d8a [Inference Endpoints] Omit model.task instead of sending null on create (#4...
• 909b162 [Inference Endpoints] Add hf endpoints hardware to list available instances...
• 5ac9711 Do not use a redirect's Content-Length as file size in get_hf_file_metadata (...
• 99aba55 [Docs] Normalize malformed docstring parameter entries (#4623)
• 2e6c67d [Inference Providers] deepinfra: add feature-extraction (embeddings) support ...
• 7a522f0 docs: remove obsolete Repository guide references (#4679)
• aa40a65 [Download] Fix ResolvedRevision string value after pickle/copy (#4692)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

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[dependabot]

Bumps huggingface-hub from 1.24.0 to 1.28.0.

Release notes

Sourced from huggingface-hub's releases.

[v1.28.0] Hardware discovery and managed engine images for Inference Endpoints and more

🔎 Discover deployable hardware with hf endpoints hardware

Deploying an Inference Endpoint requires five hardware flags (--vendor, --region, --accelerator, --instance-type, --instance-size) whose valid values depend on each other, and until now there was no way to learn them from the CLI. The new hf endpoints hardware command lists the valid combinations along with the price per replica per hour and your namespace's accelerator quota, filtered by default to the hardware you can deploy on right now. The same data is available in the SDK via list_inference_endpoints_hardware(), which flattens the API response into InferenceEndpointHardware objects you can filter programmatically.

>>> hf endpoints hardware --vendor aws --region eu-west-1
VENDOR REGION ACCELERATOR INSTANCE_TYPE INSTANCE_SIZE MEMORY_GB GPU_MEMORY_GB PRICE_PER_HOUR QUOTA STATUS
------ --------- ----------- ------------- ------------- --------- ------------- -------------- ----- ---------
aws eu-west-1 cpu intel-spr x1 2.0 0.033 0/60 available
aws eu-west-1 cpu intel-spr x2 4.0 0.067 0/60 available
aws eu-west-1 gpu nvidia-a10g x1 30.0 24 1.0 0/16 available
aws eu-west-1 gpu nvidia-t4 x1 15.0 16 0.5 1/30 available

• [Inference Endpoints] Add hf endpoints hardware to list available instances by @​hanouticelina in #4672

🚀 Managed engine images and multi-accelerator parallelism for Inference Endpoints

custom_image now accepts the engine-specific container types supported by the API: key the dictionary with the engine name (vLLM, sGLang, tgi, tei, llamacpp, hfServe, ...) instead of leaving it flat, and each engine takes the usual container fields plus its own tuning options. Any dict without a top-level url is forwarded to the API untouched, so engines added to the API later will work without upgrading huggingface_hub, and update_inference_endpoint now handles the same payload shapes as create_inference_endpoint. On the CLI, hf endpoints deploy and hf endpoints update gain --engine, --tensor-parallel-size and --data-parallel-size, and update also accepts --custom-image, --health-route and --port. This matters because vLLM and SGLang default to a single accelerator while an endpoint is allocated every accelerator of its instance — the API now rejects that misconfiguration, and these flags are how you set things right.

$ hf endpoints deploy gpt-oss-120b-vllm --repo openai/gpt-oss-120b --framework custom \
--accelerator gpu --instance-size x8 --instance-type nvidia-h200 --region us-east-1 --vendor aws \
--engine vllm --custom-image vllm/vllm-openai:v0.23.0 --tensor-parallel-size 8
Retune a running endpoint
$ hf endpoints update gpt-oss-120b-vllm --tensor-parallel-size 4 --data-parallel-size 2

💔 Breaking change:huggingface_hub.constants.INFERENCE_ENDPOINT_IMAGE_KEYS is removed. It was never exported at the package root nor documented, but code reading it directly will now get an AttributeError.

• [Inference Endpoints] Support managed engine images in custom_image by @​hanouticelina in #4671
• [CLI] Add --tensor-parallel-size / --data-parallel-size to hf endpoints deploy and update by @​moon-bot-app[bot] in #4661

🤖 Inference

• [Inference Providers] deepinfra: add text-to-speech support by @​ovuruska in #4559
• [Inference Providers] deepinfra: add feature-extraction support by @​ovuruska in #4656

🖥️ CLI

• [CLI] Keep hf extensions off the metered GitHub REST API by @​hanouticelina in #4659

🐛 Bug and typo fixes

• [CLI] Fix scheduled upload of a single file in a subfolder by @​dfedoryshchev in #4619
• [Download] Fix tqdm_class ignored by the Xet transfer bar by @​bharadwaj-pendyala in #4647

... (truncated)

Commits

• b2da2d4 Release: v1.28.0
• a718e44 Release: v1.28.0.rc0
• 7105c3d [CLI] Add --tensor-parallel-size / --data-parallel-size to `hf endpoints depl...
• a3d9d8a [Inference Endpoints] Omit model.task instead of sending null on create (#4...
• 909b162 [Inference Endpoints] Add hf endpoints hardware to list available instances...
• 5ac9711 Do not use a redirect's Content-Length as file size in get_hf_file_metadata (...
• 99aba55 [Docs] Normalize malformed docstring parameter entries (#4623)
• 2e6c67d [Inference Providers] deepinfra: add feature-extraction (embeddings) support ...
• 7a522f0 docs: remove obsolete Repository guide references (#4679)
• aa40a65 [Download] Fix ResolvedRevision string value after pickle/copy (#4692)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

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You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[dependabot]

Bumps huggingface-hub from 1.24.0 to 1.28.0.

Release notes

Sourced from huggingface-hub's releases.

[v1.28.0] Hardware discovery and managed engine images for Inference Endpoints and more

🔎 Discover deployable hardware with hf endpoints hardware

Deploying an Inference Endpoint requires five hardware flags (--vendor, --region, --accelerator, --instance-type, --instance-size) whose valid values depend on each other, and until now there was no way to learn them from the CLI. The new hf endpoints hardware command lists the valid combinations along with the price per replica per hour and your namespace's accelerator quota, filtered by default to the hardware you can deploy on right now. The same data is available in the SDK via list_inference_endpoints_hardware(), which flattens the API response into InferenceEndpointHardware objects you can filter programmatically.

>>> hf endpoints hardware --vendor aws --region eu-west-1
VENDOR REGION ACCELERATOR INSTANCE_TYPE INSTANCE_SIZE MEMORY_GB GPU_MEMORY_GB PRICE_PER_HOUR QUOTA STATUS
------ --------- ----------- ------------- ------------- --------- ------------- -------------- ----- ---------
aws eu-west-1 cpu intel-spr x1 2.0 0.033 0/60 available
aws eu-west-1 cpu intel-spr x2 4.0 0.067 0/60 available
aws eu-west-1 gpu nvidia-a10g x1 30.0 24 1.0 0/16 available
aws eu-west-1 gpu nvidia-t4 x1 15.0 16 0.5 1/30 available

• [Inference Endpoints] Add hf endpoints hardware to list available instances by @​hanouticelina in #4672

🚀 Managed engine images and multi-accelerator parallelism for Inference Endpoints

custom_image now accepts the engine-specific container types supported by the API: key the dictionary with the engine name (vLLM, sGLang, tgi, tei, llamacpp, hfServe, ...) instead of leaving it flat, and each engine takes the usual container fields plus its own tuning options. Any dict without a top-level url is forwarded to the API untouched, so engines added to the API later will work without upgrading huggingface_hub, and update_inference_endpoint now handles the same payload shapes as create_inference_endpoint. On the CLI, hf endpoints deploy and hf endpoints update gain --engine, --tensor-parallel-size and --data-parallel-size, and update also accepts --custom-image, --health-route and --port. This matters because vLLM and SGLang default to a single accelerator while an endpoint is allocated every accelerator of its instance — the API now rejects that misconfiguration, and these flags are how you set things right.

$ hf endpoints deploy gpt-oss-120b-vllm --repo openai/gpt-oss-120b --framework custom \
--accelerator gpu --instance-size x8 --instance-type nvidia-h200 --region us-east-1 --vendor aws \
--engine vllm --custom-image vllm/vllm-openai:v0.23.0 --tensor-parallel-size 8
Retune a running endpoint
$ hf endpoints update gpt-oss-120b-vllm --tensor-parallel-size 4 --data-parallel-size 2

💔 Breaking change:huggingface_hub.constants.INFERENCE_ENDPOINT_IMAGE_KEYS is removed. It was never exported at the package root nor documented, but code reading it directly will now get an AttributeError.

• [Inference Endpoints] Support managed engine images in custom_image by @​hanouticelina in #4671
• [CLI] Add --tensor-parallel-size / --data-parallel-size to hf endpoints deploy and update by @​moon-bot-app[bot] in #4661

🤖 Inference

• [Inference Providers] deepinfra: add text-to-speech support by @​ovuruska in #4559
• [Inference Providers] deepinfra: add feature-extraction support by @​ovuruska in #4656

🖥️ CLI

• [CLI] Keep hf extensions off the metered GitHub REST API by @​hanouticelina in #4659

🐛 Bug and typo fixes

• [CLI] Fix scheduled upload of a single file in a subfolder by @​dfedoryshchev in #4619
• [Download] Fix tqdm_class ignored by the Xet transfer bar by @​bharadwaj-pendyala in #4647

... (truncated)

Commits

• b2da2d4 Release: v1.28.0
• a718e44 Release: v1.28.0.rc0
• 7105c3d [CLI] Add --tensor-parallel-size / --data-parallel-size to `hf endpoints depl...
• a3d9d8a [Inference Endpoints] Omit model.task instead of sending null on create (#4...
• 909b162 [Inference Endpoints] Add hf endpoints hardware to list available instances...
• 5ac9711 Do not use a redirect's Content-Length as file size in get_hf_file_metadata (...
• 99aba55 [Docs] Normalize malformed docstring parameter entries (#4623)
• 2e6c67d [Inference Providers] deepinfra: add feature-extraction (embeddings) support ...
• 7a522f0 docs: remove obsolete Repository guide references (#4679)
• aa40a65 [Download] Fix ResolvedRevision string value after pickle/copy (#4692)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)