Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Anime
Base Model
Landscape
BakingBeans
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/Ambrosia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Ambrosia with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/Ambrosia", 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
Update text_encoder/config.json
Browse files- text_encoder/config.json +1 -1
text_encoder/config.json
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@@ -15,7 +15,7 @@
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"max_position_embeddings": 77,
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"model_type": "clip_text_model",
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"num_attention_heads": 12,
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"num_hidden_layers":
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"pad_token_id": 1,
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"projection_dim": 768,
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"torch_dtype": "float16",
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"max_position_embeddings": 77,
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"model_type": "clip_text_model",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"projection_dim": 768,
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"torch_dtype": "float16",
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