Text Generation
PEFT
Safetensors
English
medical
biomedical
adverse-drug-events
ade
pharmacovigilance
distillation
lora
llama-3.1
conversational
Eval Results (legacy)
Instructions to use Ventali/llama31-8b-ade-sft-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ventali/llama31-8b-ade-sft-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "Ventali/llama31-8b-ade-sft-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e77e1f2e8ac96e07e9457b7b25435317615f9671eb1ff5c4de569922524cf06
- Size of remote file:
- 336 MB
- SHA256:
- 3a846d9693f4bc75f02e0b9e7b846e50d37bca3656051eae0d1faf125bb0b9ee
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