Instructions to use mitultiwari/mistral7binstruct_summarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mitultiwari/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, "mitultiwari/mistral7binstruct_summarize") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4327321f3ca52e04bea8b64d2cd5b6bb53c080c3b0153d8b4cdd0b607432f4f6
- Size of remote file:
- 4.92 kB
- SHA256:
- 31bcea126e961673c26009cec18453ab73e149c638b0c4b63ad4b97aebb6fc91
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.