Instructions to use prodip1023/mistral-finetuned-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prodip1023/mistral-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, "prodip1023/mistral-finetuned-samsum") - Notebooks
- Google Colab
- Kaggle
mistral-finetuned-samsum / runs /Oct20_18-01-15_188a8d8eb15d /events.out.tfevents.1729447899.188a8d8eb15d.20490.0
- Xet hash:
- 5d480b3ade0274b711c79cc32a4302dace403bdcfed4bfb22c0c7a655c09c899
- Size of remote file:
- 6.75 kB
- SHA256:
- 909671e9a7af1ee723a995e3229c08b0984d4eb46162c2e7ed677982f2f80c70
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.