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 /Aug26_10-52-41_fastgpuserv /events.out.tfevents.1724651569.fastgpuserv.681719.0
- Xet hash:
- 27dd4770e1aebc388ad3eca66d1e0288e060166ebff8c678b9494e3f701d5c57
- Size of remote file:
- 15.4 kB
- SHA256:
- 0f615ddafcc147fa420634d59cb13a148d2efce66b9e381be5d4dfd980d7a8ea
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