Text-to-Image
Transformers
Safetensors
Hunyuan
text-generation
hunyuan
quantization
nf4
comfyui
custom-nodes
autoregressive
DiT
HunyuanImage-3.0
instruct
image-editing
bitsandbytes
4bit
custom_code
4-bit precision
Instructions to use EricRollei/HunyuanImage-3.0-Instruct-NF4-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EricRollei/HunyuanImage-3.0-Instruct-NF4-v2 with Transformers:
# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("EricRollei/HunyuanImage-3.0-Instruct-NF4-v2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "HunyuanImage-3.0-Instruct", | |
| "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, | |
| "modules_kept_bf16": [ | |
| "vae", | |
| "vision_model", | |
| "vision_aligner", | |
| "patch_embed", | |
| "final_layer", | |
| "time_embed", | |
| "time_embed_2", | |
| "timestep_emb", | |
| "attention_projections" | |
| ], | |
| "notes": "Instruct model with vision encoder kept at BF16 for image understanding quality.", | |
| "attention_layers_quantized": false | |
| } |