Text Classification
Transformers
Safetensors
English
Polish
qwen3_5_text
text-generation
nvfp4
fp4
compressed-tensors
vllm
quantized
tentaguard
guard
security
prompt-injection
tentaflow
Instructions to use TentaFlow/TentaGuard-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TentaFlow/TentaGuard-NVFP4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TentaFlow/TentaGuard-NVFP4")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TentaFlow/TentaGuard-NVFP4") model = AutoModelForCausalLM.from_pretrained("TentaFlow/TentaGuard-NVFP4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| default_stage: | |
| default_modifiers: | |
| QuantizationModifier: | |
| targets: [Linear] | |
| ignore: [lm_head] | |
| scheme: NVFP4 | |
| bypass_divisibility_checks: false | |