Instructions to use deepset/tinyroberta-6l-768d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/tinyroberta-6l-768d 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="deepset/tinyroberta-6l-768d")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/tinyroberta-6l-768d") model = AutoModelForQuestionAnswering.from_pretrained("deepset/tinyroberta-6l-768d", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/tinyroberta-6l-768d: direct link, hf CLI and curl.
- Browser
- Download file 326 MB
-
https://huggingface.co/deepset/tinyroberta-6l-768d/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepset/tinyroberta-6l-768d/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/tinyroberta-6l-768d/resolve/main/pytorch_model.bin
326 MB
- Xet hash:
- e4fc1f24319257cfa4770cda075f3e11f51ed41b7053bcaf69dbbe4f25c08704
- Size of remote file:
- 326 MB
- SHA256:
- 3fd7a0c8706549570e1a5af2f11b2661e8d8987a96b40649a4311303e9490148
路
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