Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/Financial_laxo_2e-5_16_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/Financial_laxo_2e-5_16_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/Financial_laxo_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/Financial_laxo_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/Financial_laxo_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd7cd04eb6b4af05304890fe5ae0b0637629bf2b3d023b46fb8dfddd8b36d1d2
- Size of remote file:
- 439 MB
- SHA256:
- 362ea41ed03d08f97e4088aefe1ac79a6ce417877453c8f67011f90f8429ee4b
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