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 training_args.bin from sunitha/output_files: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/sunitha/output_files/resolve/main/training_args.bin
- Command line
-
hf download hf://sunitha/output_files/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sunitha/output_files/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- e1d3afd8f25e75909eb27912987f661171e7b6f6b9e0c010db7aac92817982cf
- Size of remote file:
- 2.93 kB
- SHA256:
- faeb7562094a5d9edacff859ab0f12742876752fcbbacd5b0a76ef6bf4f02dea
路
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