Text Classification
Transformers
Safetensors
prompt-complexity
feature-extraction
regression
prompt
complexity-estimation
semantic-routing
llm-routing
custom_code
Instructions to use ilya-kolchinsky/PromptComplexityEstimator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ilya-kolchinsky/PromptComplexityEstimator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ilya-kolchinsky/PromptComplexityEstimator", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ilya-kolchinsky/PromptComplexityEstimator", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ilya-kolchinsky/PromptComplexityEstimator: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/ilya-kolchinsky/PromptComplexityEstimator/resolve/main/tokenizer.json
- Command line
-
hf download hf://ilya-kolchinsky/PromptComplexityEstimator/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/ilya-kolchinsky/PromptComplexityEstimator/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.