Text-to-Image
Transformers
Safetensors
Hunyuan
text-generation
hunyuan
quantization
nf4
comfyui
custom-nodes
autoregressive
DiT
HunyuanImage-3.0
bitsandbytes
4bit
custom_code
4-bit precision
Instructions to use dong16/HunyuanImage-3-NF4-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dong16/HunyuanImage-3-NF4-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("dong16/HunyuanImage-3-NF4-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download quantization_metadata.json from dong16/HunyuanImage-3-NF4-v2: direct link, hf CLI and curl.
- Browser
- Download file 366 Bytes
-
https://huggingface.co/dong16/HunyuanImage-3-NF4-v2/resolve/main/quantization_metadata.json
- Command line
-
hf download hf://dong16/HunyuanImage-3-NF4-v2/quantization_metadata.json
-
curl -L -o quantization_metadata.json https://huggingface.co/dong16/HunyuanImage-3-NF4-v2/resolve/main/quantization_metadata.json
366 Bytes
| { | |
| "quantization_method": "bitsandbytes_nf4", | |
| "load_in_4bit": true, | |
| "bnb_4bit_quant_type": "nf4", | |
| "bnb_4bit_use_double_quant": true, | |
| "bnb_4bit_compute_dtype": "torch.bfloat16", | |
| "expected_vram_gb": 45, | |
| "notes": "Load with BitsAndBytesConfig for NF4 quantization. Attention layers kept in full precision.", | |
| "attention_layers_quantized": false | |
| } |