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 training_args.bin from sunitha/CV_Merge_DS: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/sunitha/CV_Merge_DS/resolve/main/training_args.bin
- Command line
-
hf download hf://sunitha/CV_Merge_DS/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sunitha/CV_Merge_DS/resolve/main/training_args.bin
3.18 kB
- Xet hash:
- 5bc6f8ea669292b4f87ea4fb20b6524f98743486e32443eab41c9b3bfa193b0a
- Size of remote file:
- 3.18 kB
- SHA256:
- 5020f0362ff774b2df9eaf0cca6cd07fe56675ceae2632817255c55c83ad358a
路
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