Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/siebert_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/siebert_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/siebert_laxo_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/siebert_laxo_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/siebert_laxo_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60b99be3eebd69cda87a772797fcddd13e30bc1227026db619f93facca4c9684
- Size of remote file:
- 3.9 kB
- SHA256:
- 24330e07a55cb0f6a58d34fcbb54b96b9679b49f255f865ed5dd108fb33a5d92
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