Instructions to use mattbit/distilbert-tweet-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mattbit/distilbert-tweet-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mattbit/distilbert-tweet-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mattbit/distilbert-tweet-sentiment") model = AutoModelForSequenceClassification.from_pretrained("mattbit/distilbert-tweet-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04677f8451b420318895bb23ae700be0437c91d558a8b3375a28a3bfe0538553
- Size of remote file:
- 3.96 kB
- SHA256:
- 662eb5bebd3e9fc147ffb7fad55f16f7431d019b26704b3ad8c38f214fbc2c37
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