Instructions to use JasonYANG170/Qwen2.5-0.5B-Instruct-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use JasonYANG170/Qwen2.5-0.5B-Instruct-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'JasonYANG170/Qwen2.5-0.5B-Instruct-ONNX');
Qwen2.5-0.5B-Instruct ONNX
ONNX export for browser/local inference. Converted from
Qwen/Qwen2.5-0.5B-Instruct at revision 7ae557604adf67be50417f59c2c2f167def9a775. No fine-tuning.
- Task:
text-generation-with-past - Precision:
fp32,fp16 - Context:
32768tokens - Runtime: Transformers.js / ONNX Runtime; select the dtype explicitly
- Files: weights in
onnx/; tokenizer and configuration at the repository root - Provenance and hashes: build-manifest.json, SHA256SUMS
FP32 requires both onnx/model.onnx and onnx/model.onnx_data. FP16 uses
onnx/model_fp16.onnx. INT8 and Q4 weights are not included.
Validation reports and helper scripts are in validation/ and tools/.
See the upstream model card for model details and licensing.
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