Text-to-Image
Transformers
Safetensors
Hunyuan
text-generation
hunyuan
quantization
int8
comfyui
custom-nodes
autoregressive
DiT
HunyuanImage-3.0
instruct
image-editing
bitsandbytes
custom_code
8-bit precision
Instructions to use EricRollei/HunyuanImage-3.0-Instruct-INT8-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-INT8-v2 with Transformers:
# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("EricRollei/HunyuanImage-3.0-Instruct-INT8-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 666 Bytes
12ab833 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"model_type": "HunyuanImage-3.0-Instruct",
"quantization_method": "bitsandbytes_int8",
"load_in_8bit": true,
"llm_int8_threshold": 6.0,
"expected_vram_gb": 95,
"expected_total_memory_gb": 100,
"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,
"quality_vs_nf4": "Significantly better - approximately 2x memory for ~98% quality retention"
} |