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_13-11-19_fastgpuserv /events.out.tfevents.1724573484.fastgpuserv.2039446.0
- Xet hash:
- 155e4840169160bad9098a460130be598b47f6e7e62833b6f75d2f525f36a6c3
- Size of remote file:
- 6.08 kB
- SHA256:
- 339e20ee57f60c47413524e27c5cd52de457b6f8de8fb8edc3ad397528d5f3a2
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