Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use mattmcclean/distilbert-base-uncased-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mattmcclean/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mattmcclean/distilbert-base-uncased-finetuned-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mattmcclean/distilbert-base-uncased-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("mattmcclean/distilbert-base-uncased-finetuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mattmcclean/distilbert-base-uncased-finetuned-emotion: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/mattmcclean/distilbert-base-uncased-finetuned-emotion/resolve/main/training_args.bin
- Command line
-
hf download hf://mattmcclean/distilbert-base-uncased-finetuned-emotion/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mattmcclean/distilbert-base-uncased-finetuned-emotion/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- d23fe24e6b27a803d6d8ad25c479939e95a2500edfdeed5140028a24bdd3c0f6
- Size of remote file:
- 2.86 kB
- SHA256:
- e0f3070d8ea1456661c387a4d0003f81469b8598bff900198503560c3efd4e15
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