Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/Financial_estricto_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_estricto_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_estricto_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/Financial_estricto_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/Financial_estricto_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c82a61fb6d8169a47c4f503785d7d0178934526d40544f010c9993847a5e431
- Size of remote file:
- 3.96 kB
- SHA256:
- 91559b678cf9dcf69d8de6c48b38c417649a6c6b650862b6a1baedd436316319
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