Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use sfarrukhm/distilbert-base-uncased-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sfarrukhm/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sfarrukhm/distilbert-base-uncased-finetuned-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sfarrukhm/distilbert-base-uncased-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("sfarrukhm/distilbert-base-uncased-finetuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 772a1c74e7b8b08f759fdcb509a4bcdef177874b3660a530427edc290fbb9ee2
- Size of remote file:
- 5.18 kB
- SHA256:
- 29fea123df6800d82399f604e50ecdea257baf454dd576f9312bcdf2e6c94705
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.