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
Commit History
-
Upload RobertaForQuestionAnswering (#4)
- Upload RobertaForQuestionAnswering (2b101cd98f559492fdb98632939b91be42617755) Co-authored-by: Aaron Reich <agr505@users.noreply.huggingface.co>136d175 -
Upload RobertaForQuestionAnswering (#3)
- Upload RobertaForQuestionAnswering (f98b54688918720e050bc0206f65706077c2115f) Co-authored-by: Aaron Reich <agr505@users.noreply.huggingface.co>9e2161f -
Upload tokenizer (#2)
- Upload tokenizer (d8192413a437e6f1299a4b4693465d3ac3289d6e) Co-authored-by: Aaron Reich <agr505@users.noreply.huggingface.co>0192db4 -
Upload RobertaForQuestionAnswering (#1)
- Upload RobertaForQuestionAnswering (0333ff7403c3a4184b6619cc814321278c35e0eb) Co-authored-by: Aaron Reich <agr505@users.noreply.huggingface.co>68d7cfd -
initial commit
0401120