Instructions to use bilkultheek/Cold-Data-LLama-2-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bilkultheek/Cold-Data-LLama-2-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "bilkultheek/Cold-Data-LLama-2-7B") - Notebooks
- Google Colab
- Kaggle
Cold-Data-LLama-2-7B / runs /Aug09_10-22-52_fastgpuserv /events.out.tfevents.1723180978.fastgpuserv.502349.0
- Xet hash:
- be90f7f1ac12cb21fce848cbd474488885855ee3981a46fab50a2870407b3d90
- Size of remote file:
- 33.8 kB
- SHA256:
- 12e057a969fc78b376b9746b1715f59685f9c9859633a49534ccb7d269f57827
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