Text Classification
PEFT
Safetensors
English
sentiment-analysis
financial-nlp
llama
lora
qlora
4-bit precision
bitsandbytes
Eval Results (legacy)
Instructions to use NunoMotaRicardo/llama-3.1-8b-financial-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use NunoMotaRicardo/llama-3.1-8b-financial-sentiment with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "NunoMotaRicardo/llama-3.1-8b-financial-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2630d8cdef4cc0c54605610017d1d9fdb1fec94879819dcd535246b0d6fc4a7c
- Size of remote file:
- 85.8 MB
- SHA256:
- dda377d203f02d017e71c69d626b7368197d660532afc6a4f37e44eee3394e22
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.