Instructions to use p1atdev/pvc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use p1atdev/pvc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("p1atdev/pvc", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece, best quality, high quality, 1girl, cat ears, silver, blue, frills, bow, looking at viewer, ultra detailed" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 555 Bytes
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"architectures": [
"CLIPTextModel"
],
"attention_dropout": 0.0,
"bos_token_id": 0,
"dropout": 0.0,
"eos_token_id": 2,
"hidden_act": "gelu",
"hidden_size": 1024,
"initializer_factor": 1.0,
"initializer_range": 0.02,
"intermediate_size": 4096,
"layer_norm_eps": 1e-05,
"max_position_embeddings": 77,
"model_type": "clip_text_model",
"num_attention_heads": 16,
"num_hidden_layers": 23,
"pad_token_id": 1,
"projection_dim": 512,
"torch_dtype": "float32",
"transformers_version": "4.25.1",
"vocab_size": 49408
}
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