Instructions to use Xenova/tiny-random-RoFormerForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/tiny-random-RoFormerForQuestionAnswering with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('question-answering', 'Xenova/tiny-random-RoFormerForQuestionAnswering');
Commit History
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Add/update the quantized ONNX model files and README.md for Transformers.js v3
Verified signature## Applied Quantizations ### ✅ Based on `model.onnx` *with* slimming ↳ ✅ `int8`: `model_int8.onnx` (added) ↳ ✅ `uint8`: `model_uint8.onnx` (added) ↳ ✅ `q4`: `model_q4.onnx` (added) ↳ ✅ `q4f16`: `model_q4f16.onnx` (added) ↳ ✅ `bnb4`: `model_bnb4.onnx` (added) ### ✅ Based on `model.onnx` *with* slimming ↳ ✅ `int8`: `model_int8.onnx` (added) ↳ ✅ `uint8`: `model_uint8.onnx` (added) ↳ ✅ `q4`: `model_q4.onnx` (added) ↳ ✅ `q4f16`: `model_q4f16.onnx` (added) ↳ ✅ `bnb4`: `model_bnb4.onnx` (added)3f3e772
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[Automated] Update base model metadata
Verified signatureSet base model to "hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering"f4ade82
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Upload fp16 ONNX weights
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Upload folder using huggingface_hub
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Upload README.md with huggingface_hub
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initial commit
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