Instructions to use hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering 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="hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering: direct link, hf CLI and curl.
- Browser
- Download file 349 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering/resolve/refs%2Fpr%2F1/model.safetensors
349 kB
- Xet hash:
- b9e1a804e6077b76f95eb3f2093fb9b1ddd0883a4bfedcd069648fdeb5f9f45f
- Size of remote file:
- 349 kB
- SHA256:
- 2cd39beb1fa929bf7523e65e17a464aaaf4c2b0b1f24b77bf56812c441d5534a
路
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