Text Classification
Transformers
Safetensors
PyTorch
English
distilbert
emotion-classification
twitter
Eval Results (legacy)
text-embeddings-inference
Instructions to use znmor9365/Twitter_DistilBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use znmor9365/Twitter_DistilBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="znmor9365/Twitter_DistilBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("znmor9365/Twitter_DistilBERT") model = AutoModelForSequenceClassification.from_pretrained("znmor9365/Twitter_DistilBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5753a0df3c3ede91815160416ed639a2426be0b644bc094da7bf3cb9b9351ffe
- Size of remote file:
- 5.27 kB
- SHA256:
- 280fba506dcc0e2f9fce2d000ef3e00aae68420e3e53ff8f721f188c778c4f54
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