Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/emotion_trained_42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/emotion_trained_42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/emotion_trained_42")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/emotion_trained_42") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/emotion_trained_42", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from marcolatella/emotion_trained_42: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/marcolatella/emotion_trained_42/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://marcolatella/emotion_trained_42/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/marcolatella/emotion_trained_42/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 278508524494cf9dd3dea589c75d6159f28674e2957f16ceeed0c22f7dfa9eab
- Size of remote file:
- 268 MB
- SHA256:
- dcefbed2987dd8a4c3d62054572e8f8edceb7ea74c200e95cb9b0c4b458a87db
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