Text Classification
Transformers
Safetensors
gemma3_text
data-filter
political-science
text-embeddings-inference
Instructions to use TerenceLau/galahad-classifier-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TerenceLau/galahad-classifier-300m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TerenceLau/galahad-classifier-300m")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TerenceLau/galahad-classifier-300m") model = AutoModelForSequenceClassification.from_pretrained("TerenceLau/galahad-classifier-300m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from TerenceLau/galahad-classifier-300m: direct link, hf CLI and curl.
- Browser
- Download file 1.16 MB
-
https://huggingface.co/TerenceLau/galahad-classifier-300m/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://TerenceLau/galahad-classifier-300m/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/TerenceLau/galahad-classifier-300m/resolve/main/tokenizer_config.json
1.16 MB
File too large to display, you can check the raw version instead.