Instructions to use lvcalucioli/zephyr-7b-beta_question-answering_question-answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lvcalucioli/zephyr-7b-beta_question-answering_question-answering with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(base_model, "lvcalucioli/zephyr-7b-beta_question-answering_question-answering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dc2697bab1d54998ca969aaac308fa22a09008c664bb457b6c901acaa977846
- Size of remote file:
- 553 MB
- SHA256:
- 5ac33e2e0c678d9dd9936071a1a67e94b19d9a87beac5540cd722f1595ef133c
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