Instructions to use sunitha/CV_Custom_DS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sunitha/CV_Custom_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_Custom_DS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sunitha/CV_Custom_DS") model = AutoModelForQuestionAnswering.from_pretrained("sunitha/CV_Custom_DS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sunitha/CV_Custom_DS: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/sunitha/CV_Custom_DS/resolve/main/training_args.bin
- Command line
-
hf download hf://sunitha/CV_Custom_DS/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sunitha/CV_Custom_DS/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 2d4c4bf34a374ab809d5129e04d1a2966c4c572c0e554f96519bb980adea97f0
- Size of remote file:
- 3.06 kB
- SHA256:
- a0023f856727de8b8f652763647ea63a312562bd2a599ae9bf7f5298920948f7
路
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