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 /Aug20_23-57-27_fastgpuserv /events.out.tfevents.1724193656.fastgpuserv.1412094.1
- Xet hash:
- 4afa1a844ef183fd5f6f41eb423a8250b268af42d6d0e871f1ae278b0a575727
- Size of remote file:
- 7.41 kB
- SHA256:
- 0dd21beb2705c281008c444c908b3bbc99f8b40a7608ab8cc9afd0c2307affc3
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