Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use dsmsb/tweet-classification-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsmsb/tweet-classification-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dsmsb/tweet-classification-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dsmsb/tweet-classification-v1") model = AutoModelForSequenceClassification.from_pretrained("dsmsb/tweet-classification-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 340276e880299008dd391736fabe07d5d1add4e2049a0fea286cf10978c64886
- Size of remote file:
- 3.96 kB
- SHA256:
- 3ea4a1f33be0260e966607993992a310557b4946f6c38d2d31d28fd2f1fec091
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