Text Classification
Transformers
Safetensors
gemma3_text
Generated from Trainer
text-embeddings-inference
Instructions to use staturecrane/chat_router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use staturecrane/chat_router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="staturecrane/chat_router")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("staturecrane/chat_router") model = AutoModelForSequenceClassification.from_pretrained("staturecrane/chat_router", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a9f7aef99f8748ac67827c9e4f112205a0913a62c5668cec1c86b117d7be016
- Size of remote file:
- 5.2 kB
- SHA256:
- 7eff3a0e89fb6fffe1d833b8028548a6cd611f50c9bbce783044aac151d0f0f9
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