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_13-37-11_fastgpuserv /events.out.tfevents.1724575034.fastgpuserv.2094483.1
- Xet hash:
- 2ae486c6391f78a3f8e6d11761ddf67a1e02a170de5a20075f8f6df15c8a8846
- Size of remote file:
- 6.08 kB
- SHA256:
- 23cecba266d80cb784f471afcfa3c8022a76a8e0f206d63fec76efcfe2f4777c
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