Instructions to use Intel/dynamic_tinybert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/dynamic_tinybert with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Intel/dynamic_tinybert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Intel/dynamic_tinybert") model = AutoModelForQuestionAnswering.from_pretrained("Intel/dynamic_tinybert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Intel/dynamic_tinybert: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Intel/dynamic_tinybert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Intel/dynamic_tinybert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Intel/dynamic_tinybert/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 61463f937b2e9f6998f0250f6ada2a9b904107ba65f25eac544efd101ace4a70
- Size of remote file:
- 268 MB
- SHA256:
- 559bc6e27704c82f08642c84a235a152983d619e9ba7e63fc2d6325c914f6e43
路
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