Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use reiffd/bert-base-phia-secondhandDescription-100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reiffd/bert-base-phia-secondhandDescription-100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reiffd/bert-base-phia-secondhandDescription-100")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reiffd/bert-base-phia-secondhandDescription-100") model = AutoModelForSequenceClassification.from_pretrained("reiffd/bert-base-phia-secondhandDescription-100") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9d49d36646d2540d607d9d049ff2e6c139b2ab31d5dd43f18b70e2fa4ae03de
- Size of remote file:
- 5.18 kB
- SHA256:
- 315922ec1dc0ebfb41df03f4a0d9e3512ae8a6fc83758c5c44b5bb157264434a
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