Instructions to use llm-wizard/mistral7binstruct_summarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use llm-wizard/mistral7binstruct_summarize with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "llm-wizard/mistral7binstruct_summarize") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b88fa5d58f4cb7440200fb90adb35083a84bb4fd82bc8514dd2d85d6458d37a
- Size of remote file:
- 4.92 kB
- SHA256:
- 7e724461c3b1bc07935f66fbe93443f4fbd5943ebfe5a0ec0629c37875208d8f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.