Text Classification
Transformers
PyTorch
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use 501Good/distilbert-base-cased-finetuned-tweeteval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 501Good/distilbert-base-cased-finetuned-tweeteval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="501Good/distilbert-base-cased-finetuned-tweeteval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("501Good/distilbert-base-cased-finetuned-tweeteval") model = AutoModelForSequenceClassification.from_pretrained("501Good/distilbert-base-cased-finetuned-tweeteval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 769962815aa2c3251f4081b600d49397b31e5fccc4bd63fd47d8188ea4219591
- Size of remote file:
- 263 MB
- SHA256:
- 3f4f7b8c6815215a95bb9e7ae88e4319b8de0f18973094f68f85e131f63e420f
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