Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use 3dalgo/tal_text_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 3dalgo/tal_text_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="3dalgo/tal_text_classification_model", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("3dalgo/tal_text_classification_model") model = AutoModelForSequenceClassification.from_pretrained("3dalgo/tal_text_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 771056c5175b0eacff7901d4add515c7eb6a4106aeb3a74c08e530ebf4bcba3a
- Size of remote file:
- 268 MB
- SHA256:
- 95048bac6e34067dc16319d68703bddf255b950caa110e934a5de42acb7b73ff
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