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:
- 238912c783c5274370d7c09996476384dbfe0319f04b4708d743518a9f794f85
- Size of remote file:
- 3.96 kB
- SHA256:
- 093b02b34542d7f39392038462592ca784aa8531fe1ceb4bf37164675e2c8062
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