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 pytorch_model.bin from SanayCo/model_output: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/SanayCo/model_output/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://SanayCo/model_output@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SanayCo/model_output/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- be03463351c51a16e6883f42ac41b9526dd3747c44ac90104c944112a9df05fd
- Size of remote file:
- 438 MB
- SHA256:
- d5c3e6ff153a671f52300cd8f81fcd4b4f1244be3a8a1c5b7a31bf5922705e7a
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