Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use wildercb/bert-s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wildercb/bert-s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wildercb/bert-s")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wildercb/bert-s") model = AutoModelForSequenceClassification.from_pretrained("wildercb/bert-s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cb23f8c42c07f98f4b01aded76aebb9fc032cdd3dcc11473c6c666df4190df6
- Size of remote file:
- 3.58 kB
- SHA256:
- 33557a1b7d01b201c9dd96a664b881012bc9c76d39e7ffbe9fcd39688b53c6e4
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