Text Classification
Transformers
Safetensors
roberta
bertweet
sentiment-analysis
text-embeddings-inference
Instructions to use chenweiye/llm-homework-sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chenweiye/llm-homework-sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chenweiye/llm-homework-sentiment-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chenweiye/llm-homework-sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("chenweiye/llm-homework-sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
BERTweet sentiment classifier
This repository contains a vinai/bertweet-base model fine-tuned for binary sentiment classification on the small educational dataset included in the course submission.
Evaluation on the fixed 10-example test split after continued fine-tuning: accuracy 1.00, positive F1 1.00, negative F1 1.00, macro F1 1.00. The test split is very small, so this result should not be interpreted as broad generalization.
- Downloads last month
- 43