Instructions to use sunitha/CV_Merge_DS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sunitha/CV_Merge_DS 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/CV_Merge_DS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sunitha/CV_Merge_DS") model = AutoModelForQuestionAnswering.from_pretrained("sunitha/CV_Merge_DS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sunitha/CV_Merge_DS: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/sunitha/CV_Merge_DS/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sunitha/CV_Merge_DS/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sunitha/CV_Merge_DS/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- bd05451ae2f243fc88c8d3440250db88aea8ee91cfeff2c8c1be58a2be8bc8f3
- Size of remote file:
- 496 MB
- SHA256:
- 09e6080b2d08646ac8d7b6e939a11a795b7e69a56f26a8652a8850e7a7f0259e
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