Instructions to use ShimbaLLM/Dupe-R-IMG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShimbaLLM/Dupe-R-IMG with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ShimbaLLM/Dupe-R-IMG", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 2,149 Bytes
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"model_type": "duper_img",
"repo_id": "ShimbaLLM/Dupe-R-IMG",
"total_params": 297377143,
"n_tensors": 596,
"storage_dtype": "float16",
"compute_dtype": "float32",
"tensor_sections": [
"dit",
"text_encoder",
"vae"
],
"section_params": {
"dit": 104094736,
"text_encoder": 109628544,
"vae": 83653863
},
"image_size": 256,
"latent_size": 32,
"context_length": 128,
"latent_scaling_factor": 0.18215,
"components": {
"dit": {
"_class_name": "SupraDiT",
"source": "SupraLabs/Supra2-IMG",
"license": "apache-2.0",
"params": 104094736,
"latent_ch": 4,
"latent_size": 32,
"patch": 2,
"d_model": 576,
"depth": 14,
"n_heads": 9,
"mlp_ratio": 4.0,
"ctx_dim": 768,
"max_ctx": 128,
"img_size": 256
},
"text_encoder": {
"_class_name": "T5EncoderModel",
"source": "google/flan-t5-base",
"license": "apache-2.0",
"params": 109628544,
"note": "encoder stack only; decoder not bundled",
"d_model": 768,
"num_layers": 12,
"num_heads": 12,
"d_ff": 2048,
"d_kv": 64,
"feed_forward_proj": "gated-gelu",
"vocab_size": 32128,
"n_positions": 512
},
"vae": {
"_class_name": "AutoencoderKL",
"source": "stabilityai/sd-vae-ft-mse",
"license": "mit",
"params": 83653863,
"in_channels": 3,
"out_channels": 3,
"latent_channels": 4,
"block_out_channels": [
128,
256,
512,
512
],
"layers_per_block": 2,
"norm_num_groups": 32,
"act_fn": "silu",
"scaling_factor": 0.18215,
"sample_size": 256
},
"sampler": {
"type": "rectified_flow",
"time_range": [
0.0,
1.0
],
"default_steps": 50,
"default_cfg_scale": 3.0,
"default_sampler": "euler",
"supports_heun": true
}
},
"notes": "Repackaging of Supra2-IMG + flan-t5-base (encoder) + sd-vae-ft-mse. Tensors copied unmodified under dit./text_encoder./vae. prefixes; upcast to float32 at load. Not a weight blend."
}
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