Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/bert_Pfinal_2e-5_16_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/bert_Pfinal_2e-5_16_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/bert_Pfinal_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/bert_Pfinal_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/bert_Pfinal_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38d77336f6b8901c2ffdfe3314003a1411233d73f1a17dc2561879318431405f
- Size of remote file:
- 3.58 kB
- SHA256:
- 510d2b5f0eba83ab2cf60d9766b61778d99831712e9451fddcb260aa9c006c53
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