Text Classification
Transformers
ONNX
Safetensors
modernbert
prompt-injection
jailbreak-detection
llm-security
ai-agents
guardrails
text-embeddings-inference
Instructions to use usezn/Galvanize-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usezn/Galvanize-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="usezn/Galvanize-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("usezn/Galvanize-2") model = AutoModelForSequenceClassification.from_pretrained("usezn/Galvanize-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from usezn/Galvanize-2: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/usezn/Galvanize-2/resolve/main/tokenizer.json
- Command line
-
hf download hf://usezn/Galvanize-2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/usezn/Galvanize-2/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- f0cb1dc3144a86cb71499ea606cd7738022582e5fd6545c3b5c05e7cc1510e4a
- Size of remote file:
- 34.4 MB
- SHA256:
- 8334ca456f647553e290d6700ddf1a772785d135320dac839599b3c046b43ef1
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