Instructions to use philmui/mistral7binstruct_summarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use philmui/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, "philmui/mistral7binstruct_summarize") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96890379bbdb49d1a9241675c32d13670571cb938c599d2ee52b66fe984ae403
- Size of remote file:
- 4.92 kB
- SHA256:
- 256488fa11385c51297d53b699b8b5a7c4e0db45d0861f1a8b1b954fe6a5442f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.