Instructions to use ovedrive/ERNIE-Image-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ovedrive/ERNIE-Image-nf4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ovedrive/ERNIE-Image-nf4", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "ErnieImageTransformer2DModel", | |
| "_diffusers_version": "0.38.0.dev0", | |
| "_name_or_path": "./tmp_model/transformer", | |
| "eps": 1e-06, | |
| "ffn_hidden_size": 12288, | |
| "hidden_size": 4096, | |
| "in_channels": 128, | |
| "num_attention_heads": 32, | |
| "num_layers": 36, | |
| "out_channels": 128, | |
| "patch_size": 1, | |
| "qk_layernorm": true, | |
| "quantization_config": { | |
| "_load_in_4bit": true, | |
| "_load_in_8bit": false, | |
| "bnb_4bit_compute_dtype": "bfloat16", | |
| "bnb_4bit_quant_storage": "uint8", | |
| "bnb_4bit_quant_type": "nf4", | |
| "bnb_4bit_use_double_quant": true, | |
| "llm_int8_enable_fp32_cpu_offload": false, | |
| "llm_int8_has_fp16_weight": false, | |
| "llm_int8_skip_modules": [ | |
| "layers.0.self_attention.to_q", | |
| "layers.0.self_attention.to_k", | |
| "layers.0.self_attention.to_v", | |
| "layers.0.self_attention.to_out.0", | |
| "layers.0.mlp.gate_proj", | |
| "layers.0.mlp.up_proj", | |
| "layers.0.mlp.linear_fc2", | |
| "layers.35.self_attention.to_q", | |
| "layers.35.self_attention.to_k", | |
| "layers.35.self_attention.to_v", | |
| "layers.35.self_attention.to_out.0", | |
| "layers.35.mlp.gate_proj", | |
| "layers.35.mlp.up_proj", | |
| "layers.35.mlp.linear_fc2", | |
| "text_proj", | |
| "time_embedding.linear_1", | |
| "time_embedding.linear_2", | |
| "adaLN_modulation.1", | |
| "final_norm.linear", | |
| "final_linear" | |
| ], | |
| "llm_int8_threshold": 6.0, | |
| "load_in_4bit": true, | |
| "load_in_8bit": false, | |
| "quant_method": "bitsandbytes" | |
| }, | |
| "rope_axes_dim": [ | |
| 32, | |
| 48, | |
| 48 | |
| ], | |
| "rope_theta": 256, | |
| "text_in_dim": 3072 | |
| } | |