Instructions to use AlpineHealth/history-31layers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlpineHealth/history-31layers 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="AlpineHealth/history-31layers")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("AlpineHealth/history-31layers") model = AutoModelForQuestionAnswering.from_pretrained("AlpineHealth/history-31layers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AlpineHealth/history-31layers: direct link, hf CLI and curl.
- Browser
- Download file 1.77 GB
-
https://huggingface.co/AlpineHealth/history-31layers/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AlpineHealth/history-31layers/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AlpineHealth/history-31layers/resolve/main/pytorch_model.bin
1.77 GB
- Xet hash:
- 66fabaeee60122caa2a09a2960fc75274c7be368f4dd26478025ed5b57498538
- Size of remote file:
- 1.77 GB
- SHA256:
- 448d0a9cd51cac06a75788311ee9c51acbca84dd0e5c3bad525a7c3e9fcdd67e
路
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