Instructions to use anmol-unitmole/longformer-qasper-document-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anmol-unitmole/longformer-qasper-document-qa 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="anmol-unitmole/longformer-qasper-document-qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("anmol-unitmole/longformer-qasper-document-qa") model = AutoModelForQuestionAnswering.from_pretrained("anmol-unitmole/longformer-qasper-document-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload evaluation/training_summary.json with huggingface_hub
Verified signatureb0729f8 -
Upload evaluation/EVALUATION_REPORT.md with huggingface_hub
Verified signatureccf8df0 -
Upload evaluation/controlled_context_length_comparison.json with huggingface_hub
Verified signatureb43aa89 -
Upload evaluation/baseline_comparison.json with huggingface_hub
Verified signaturec8129ba