Text Classification
Transformers
TensorFlow
English
roberta
textclassisification
robertabase
sentimentanalysis
nlp
tweetanalysis
tweet
analysis
sentiment
positive
newsanalysis
text-embeddings-inference
Instructions to use AK776161/birdseye_roberta-base-tweet-eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AK776161/birdseye_roberta-base-tweet-eval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AK776161/birdseye_roberta-base-tweet-eval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AK776161/birdseye_roberta-base-tweet-eval") model = AutoModelForSequenceClassification.from_pretrained("AK776161/birdseye_roberta-base-tweet-eval") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97bc4ef92831ab24513e6f8934f2e365f32e54f4f255b16b28471a355e45a636
- Size of remote file:
- 499 MB
- SHA256:
- 4792c8ccb1fd817e20395c24b13904be6093eb61f1b72f798e6580b5f5c0d86f
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