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_13-47-07_fastgpuserv /events.out.tfevents.1724575630.fastgpuserv.2094483.5
- Xet hash:
- 86b1b07a4e500147796f8b1f2b6e736c1b831e26b1649838a3a0eab69731be50
- Size of remote file:
- 4.44 kB
- SHA256:
- d6d613233e81b43d3dfd5bfcd2e1487f2e7c7ee0fc35873bf13644d53a1aafba
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