Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ActivationAI/distilbert-base-uncased-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ActivationAI/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ActivationAI/distilbert-base-uncased-finetuned-emotion")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ActivationAI/distilbert-base-uncased-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("ActivationAI/distilbert-base-uncased-finetuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ActivationAI/distilbert-base-uncased-finetuned-emotion: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/ActivationAI/distilbert-base-uncased-finetuned-emotion/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ActivationAI/distilbert-base-uncased-finetuned-emotion/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ActivationAI/distilbert-base-uncased-finetuned-emotion/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 12e1f45876c83ed7450e03f0651c1db7bc203b23aceedc760eaa6585efa967aa
- Size of remote file:
- 268 MB
- SHA256:
- 419ad4a650c807e093f086706b5fc73f13fc3cfc7083826a6ed6084645e99345
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.