Instructions to use sunitha/output_files with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sunitha/output_files 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="sunitha/output_files")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sunitha/output_files") model = AutoModelForQuestionAnswering.from_pretrained("sunitha/output_files", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sunitha/output_files: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/sunitha/output_files/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sunitha/output_files/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sunitha/output_files/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 7fb62d6e140a1c4924d39a75e4847e47cf395bdfc7a7781cfed2c9f62ff2abb8
- Size of remote file:
- 431 MB
- SHA256:
- 8b54198e2d0c6d34250455e036117b29c005e0293723dfea306fa97691a73f95
路
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