Instructions to use neuronstarml/mistral7b-finetuned-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use neuronstarml/mistral7b-finetuned-samsum with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.1-GPTQ") model = PeftModel.from_pretrained(base_model, "neuronstarml/mistral7b-finetuned-samsum") - Notebooks
- Google Colab
- Kaggle
mistral7b-finetuned-samsum / runs /Aug17_14-42-49_df422565cbce /events.out.tfevents.1723905811.df422565cbce.6375.0
- Xet hash:
- 598e66c4b19e615884ed578ebdf4e86f3ba4e938e473e9ddbe66e03c9f1dcf12
- Size of remote file:
- 6.67 kB
- SHA256:
- ca81925fc5aaca619d26bb98405d3e2a044a9c7cc92d277070fd7a9793a27412
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.