hf_transformers_go

Pure Go implementation of Hugging Face-style transformers.

Quick compare: Python vs Go

Python (transformers.js-like usage):

fromtransformersimportpipelinegenerator=pipeline("text-generation", model="onnx-community/SmolLM2-135M-ONNX")
out=generator("What is the third planet in our solar system and who inhabits it?", max_new_tokens=32)
print(out[0]["generated_text"])

Go (this repo):

package main
import (
"fmt""log"
. "github.com/scriptmaster/hf_transformers_go/transformers"
)
varpipeline=Pipelinefuncmain() {
generator, err:=pipeline(
"text-generation",
"onnx-community/SmolLM2-135M-ONNX",
map[string]any{"dtype": "q4"},
)
iferr!=nil {
log.Println(err)
return
}
out, err:=generator([]ChatMessage{
{Role: RoleUser, Content: "What is the third planet in our solar system and who inhabits it?"},
}, map[string]any{"max_new_tokens": 32})
iferr!=nil {
log.Println(err)
return
}
fmt.Println(out[0]["generated_text"])
}

Notes:

• We auto-download config.json, tokenizer.json, ONNX weights (and .onnx_data), and optional tokenizer assets into ./models/huggingface.co/<MODEL_ID>/resolve/main/ (or CACHE_DIR if set).
• generation_config.json is parsed (if present) for eos/bos/pad IDs and default stop strings; you can also pass stop in call options.
• MODEL_FILES env can override optional asset list (comma-separated).