Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use reiffd/bert-base-phia-secondhandDescription-1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reiffd/bert-base-phia-secondhandDescription-1000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reiffd/bert-base-phia-secondhandDescription-1000")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reiffd/bert-base-phia-secondhandDescription-1000") model = AutoModelForSequenceClassification.from_pretrained("reiffd/bert-base-phia-secondhandDescription-1000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a872a96af49903536e9db54f3cf2891f1cfc9f1a1031015202a614b57ce6db4
- Size of remote file:
- 5.18 kB
- SHA256:
- c8f4c763b67c28d826c2fa04d55c04ab7bd96bf05b0e5cd21c583fa6cdc54acc
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