Instructions to use spjabech/sentiment_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use spjabech/sentiment_classification with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("gradientai/Llama-3-8B-Instruct-262k") model = PeftModel.from_pretrained(base_model, "spjabech/sentiment_classification") - Notebooks
- Google Colab
- Kaggle
File size: 229 Bytes
d97cc1d | 1 2 3 4 5 6 7 8 9 | {
"epoch": 1.0,
"total_flos": 6359033384534016.0,
"train_loss": 1.1705604413071193,
"train_runtime": 1777.143,
"train_samples": 296,
"train_samples_per_second": 0.167,
"train_steps_per_second": 0.021
} |