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_13-21-16_fastgpuserv /events.out.tfevents.1724574078.fastgpuserv.2039446.6
- Xet hash:
- 7a2575e055fbcef200a11ffc65c0ea0a55a3dd32eab8c6b41c618b32fabef522
- Size of remote file:
- 6.08 kB
- SHA256:
- 71f035a87b1d3f3f0e91533cdc4b67555f0f3e2e1e8d969b192fa50d7ff3cdf4
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