Text Classification
Transformers
Safetensors
English
bert
image-optimization
technique-routing
headroom
text-embeddings-inference
Instructions to use chopratejas/technique-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chopratejas/technique-router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chopratejas/technique-router")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chopratejas/technique-router") model = AutoModelForSequenceClassification.from_pretrained("chopratejas/technique-router", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from chopratejas/technique-router: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/chopratejas/technique-router/resolve/main/tokenizer.json
- Command line
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hf download hf://chopratejas/technique-router/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/chopratejas/technique-router/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.