Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use tinutmap/categor_ai_23_cats with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tinutmap/categor_ai_23_cats with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tinutmap/categor_ai_23_cats")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tinutmap/categor_ai_23_cats") model = AutoModelForSequenceClassification.from_pretrained("tinutmap/categor_ai_23_cats", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d57d86108cf5eacb80ee6ebba4a76e2ceed1397e8ad3cbab1fc8a4f081b2ea1
- Size of remote file:
- 5.18 kB
- SHA256:
- 740279f24fde14dd9a4be9bd5bb52a5b413875fec7cae6a4e5d4fafbcb0064c6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.