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:
- d42a835f3e7019bf0a42b44b43a7c317b012da4a8005f5cad3a631eaa1bede50
- Size of remote file:
- 14.6 kB
- SHA256:
- 5ac14e73f8e5b9769e9f003c05a28363f548f3700779fe2deb19cd368d55e7c2
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