Instructions to use eskimo7/distilbert-tweets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eskimo7/distilbert-tweets with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eskimo7/distilbert-tweets")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eskimo7/distilbert-tweets") model = AutoModelForSequenceClassification.from_pretrained("eskimo7/distilbert-tweets", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f63f7adc058d8d0e8eda392a397b2880ea831273128ae68ef17b440cb54972f8
- Size of remote file:
- 268 MB
- SHA256:
- b399de892eb0f07645f8f78a0366b598d714a91cbbd5b750f5df84e93d7089d4
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