Text Classification
Transformers
Safetensors
modernbert
feature-extraction
intent
routing
chatbot
agents
moderation
prompt-injection
off-topic
text-embeddings-inference
Instructions to use allsmart/Intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allsmart/Intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="allsmart/Intent")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("allsmart/Intent") model = AutoModel.from_pretrained("allsmart/Intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from allsmart/Intent: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/allsmart/Intent/resolve/main/tokenizer.json
- Command line
-
hf download hf://allsmart/Intent/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/allsmart/Intent/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- daf46a52874fb9b6191b9ae46a0f471904405b611f8e1d580f76c7424d343f89
- Size of remote file:
- 34.4 MB
- SHA256:
- 17f7d8b9518c403d7429ad9eeeabb6eed49c8d3311de8ef4ed5ad811381a2ced
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