Instructions to use SanayCo/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SanayCo/model_output 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="SanayCo/model_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SanayCo/model_output") model = AutoModelForQuestionAnswering.from_pretrained("SanayCo/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SanayCo/model_output: direct link, hf CLI and curl.
- Browser
- Download file 1.44 kB
-
https://huggingface.co/SanayCo/model_output/resolve/main/training_args.bin
- Command line
-
hf download hf://SanayCo/model_output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SanayCo/model_output/resolve/main/training_args.bin
1.44 kB
- Xet hash:
- 0e19ef12ae6d7d58c60ee7229f1711936378d9073b7cb3cdda2ca32196161549
- Size of remote file:
- 1.44 kB
- SHA256:
- 8a185fd1e2be81b9dddf045c4150699989e309737e3d7116fd3f0545b81e3c58
路
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