Pokemon Text To Image 2
This bla bla pipeline was finetuned from runwayml/stable-diffusion-v1-5 on the lambdalabs/pokemon-blip-captions dataset. Below are some example images generated with the finetuned pipeline using the following...
Model source
- Kind
- Other
- File size
- 319 MB–3.20 GB
- Base model
- runwayml/stable-diffusion-v1-5
- Version
- vRevision df60889
- Updated
- Oct 6, 2026
- Downloads
- 1
- Source
- Hugging Face
Source description
Text-to-image finetuning - shrikant11/pokemon_text_to_image_2
This bla bla pipeline was finetuned from runwayml/stable-diffusion-v1-5 on the lambdalabs/pokemon-blip-captions dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Pokemon with yellow eyes', 'Green colour pokemon', 'Blue colour pikacchu', 'Charlizzard', 'pikachu', 'dangerous looking pokemon']:
val_imgs_grid
Pipeline usage
You can use the pipeline like so:
from diffusers import DiffusionPipeline
import torch
pipeline = DiffusionPipeline.from_pretrained("shrikant11/pokemon_text_to_image_2", torch_dtype=torch.float16)
prompt = "Pokemon with yellow eyes"
image = pipeline(prompt).images[0]
image.save("my_image.png")
Training info
These are the key hyperparameters used during training:
- Epochs: 1
- Learning rate: 1e-05
- Batch size: 1
- Gradient accumulation steps: 1
- Image resolution: 512
- Mixed-precision: None
More information on all the CLI arguments and the environment are available on your wandb run page.
Sources
1 source
Sources
1 sourceVerified Oct 6
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Model artifacts
4 artifacts
Model artifacts
4 artifactssafety_checker/model.safetensors
safetensors · 1.13 GB · SHA-256 fb351a5ded81…fde8 · Hugging Face
Download filetext_encoder/model.safetensors
safetensors · 469 MB · SHA-256 778d02eb9e70…47c3 · Hugging Face
Download fileunet/diffusion_pytorch_model.safetensors
safetensors · 3.20 GB · SHA-256 69cf22d5569d…789e · Hugging Face
Download filevae/diffusion_pytorch_model.safetensors
safetensors · 319 MB · SHA-256 b4d2b5932bb4…4c49 · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- license: creativeml-openrail-m base_model: runwayml/stable-diffusion-v1-5 datasets: - lambdalabs/pokemon-blip-captions tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers inference: true --- # Text-to-image finetuning - shrikant11/pokemon_text_to_image_2 This bla bla pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **lambdalabs/pokemon-blip-captions** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Pokemon with yellow eyes', 'Green colour pokemon', 'Blue colour pikacchu', 'Charlizzard', 'pikachu', 'dangerous looking pokemon']:  ## Pipeline usage You can use the pipeline like so: ```python from diffusers import DiffusionPipeline import torch pipeline = DiffusionPipeline.from_pretrained("shrikant11/pokemon_text_to_image_2", torch_dtype=torch.float16) prompt = "Pokemon with yellow eyes" image = pipeline(prompt).images[0] image.save("my_image.png") ``` ## Training info These are the key hyperparameters used during training: * Epochs: 1 * Learning rate: 1e-05 * Batch size: 1 * Gradient accumulation steps: 1 * Image resolution: 512 * Mixed-precision: None More information on all the CLI arguments and the environment are available on your [`wandb` run page]().
Source context: 1 downloads · 1 likes · Pipeline text-to-image · Library diffusers · Repo shrikant11/pokemon_text_to_image_2
Source context: 16 downloads · 1 likes · Pipeline text-to-image · Library diffusers · Repo shrikant11/pokemon_text_to_image_2
