Text-to-Image
Transformers
Safetensors
Hunyuan
text-generation
hunyuan
quantization
int8
comfyui
custom-nodes
autoregressive
DiT
HunyuanImage-3.0
instruct
image-editing
bitsandbytes
distilled
custom_code
8-bit precision
Instructions to use EricRollei/HunyuanImage-3.0-Instruct-Distil-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-Distil-INT8-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("EricRollei/HunyuanImage-3.0-Instruct-Distil-INT8-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 880 Bytes
4c79057 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"model_type": "HunyuanImage-3.0-Instruct-Distil",
"quantization_method": "bitsandbytes_int8",
"load_in_8bit": true,
"llm_int8_threshold": 6.0,
"expected_vram_gb": 18,
"expected_total_memory_gb": 20,
"total_params": "80B",
"active_params": "13B (MoE)",
"modules_kept_bf16": [
"vae",
"vision_model",
"vision_aligner",
"patch_embed",
"final_layer",
"time_embed",
"time_embed_2",
"timestep_emb",
"guidance_emb",
"timestep_r_emb",
"attention_projections"
],
"distil_features": {
"cfg_distilled": true,
"meanflow": true,
"description": "Single-step CFG-free generation with meanflow"
},
"notes": "Distilled Instruct model - fast inference, single GPU friendly.",
"attention_layers_quantized": false,
"quality_vs_nf4": "Better quality than NF4 with reasonable memory"
} |