Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/siebert_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/siebert_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/siebert_estricto_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/siebert_estricto_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/siebert_estricto_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1a913bd3695865a3bac7d005b0fb2d0a7e7ada8318f247f8d9153046dbb5c6c
- Size of remote file:
- 3.96 kB
- SHA256:
- 247b04e1d0a7457cd3a6abd6e0f0c21d519d4f1e9f4d333763112bdc78ee5d6d
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