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 /Aug25_13-25-56_fastgpuserv /events.out.tfevents.1724574359.fastgpuserv.2039446.9
- Xet hash:
- df99c3b9e6929c94db94533b1afabb886217806dbe565307e8addaf3376642c1
- Size of remote file:
- 6.08 kB
- SHA256:
- 07dcb0dd548a5dbf42d7374ddee73f563c67cef4bfebcebb968c4de62ba37666
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