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 pytorch_model.bin from sunitha/CV_Custom_DS: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/sunitha/CV_Custom_DS/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://sunitha/CV_Custom_DS@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sunitha/CV_Custom_DS/resolve/refs%2Fpr%2F1/pytorch_model.bin
496 MB
- Xet hash:
- e2af9bf4ff078dd41ed8d08d50a0198c432aee210491f66e5774794ccd340d47
- Size of remote file:
- 496 MB
- SHA256:
- 6af82a9709b148c7027d2272382dc8d348892ec671c2e9804d9892bb831eb1b7
路
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