Text Classification
Transformers
Safetensors
qwen3
trackio
Generated from Trainer
text-embeddings-inference
Instructions to use akseljoonas/f2llm-sentiment-ablation-E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akseljoonas/f2llm-sentiment-ablation-E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akseljoonas/f2llm-sentiment-ablation-E")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akseljoonas/f2llm-sentiment-ablation-E") model = AutoModelForSequenceClassification.from_pretrained("akseljoonas/f2llm-sentiment-ablation-E") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ebcb72146392bf3e6eeb80e7a522dcdfaba96f56925afa3cc09b6478a55e74f
- Size of remote file:
- 11.4 MB
- SHA256:
- 92fa411c5bbebbc8cefb1e19b87a291cedd0306f723f97b20d03b35aa3599736
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