# Deprecation notice

This model was a research project focused on the effect of fine-tuning the OpenCLIP text encoder.

It has been deprecated in favour of a newer checkpoint that continued training this model.

This model remains accessible as a test comparison and possible base model for fine-tuning.

# Training data

Base model: `stabilityai/stable-diffusion-2-1`

Data: 3300 midjourney 5.1 upscaled images with their captions.

# Training parameters

Duration: 4000 steps
LR scheduler: polynomial
Batch size: 3
Text encoder: Thawed
Optimizer: 8bit ADAM
No prior loss preservation
{}
diffusers endpoints_compatible diffusers:StableDiffusionPipeline region:us
TAGS
#diffusers #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us 

# Deprecation notice

This model was a research project focused on the effect of fine-tuning the OpenCLIP text encoder.

It has been deprecated in favour of a newer checkpoint that continued training this model.

This model remains accessible as a test comparison and possible base model for fine-tuning.

# Training data

Base model: 'stabilityai/stable-diffusion-2-1'

Data: 3300 midjourney 5.1 upscaled images with their captions.

# Training parameters

Duration: 4000 steps
LR scheduler: polynomial
Batch size: 3
Text encoder: Thawed
Optimizer: 8bit ADAM
No prior loss preservation
# Deprecation notice

This model was a research project focused on the effect of fine-tuning the OpenCLIP text encoder.

It has been deprecated in favour of a newer checkpoint that continued training this model.

This model remains accessible as a test comparison and possible base model for fine-tuning. # Training data

Base model: 'stabilityai/stable-diffusion-2-1'

Data: 3300 midjourney 5.1 upscaled images with their captions. # Training parameters

Duration: 4000 steps
LR scheduler: polynomial
Batch size: 3
Text encoder: Thawed
Optimizer: 8bit ADAM
No prior loss preservation
TAGS
#diffusers #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us 
 # Deprecation notice

This model was a research project focused on the effect of fine-tuning the OpenCLIP text encoder.

It has been deprecated in favour of a newer checkpoint that continued training this model.

This model remains accessible as a test comparison and possible base model for fine-tuning. # Training data

Base model: 'stabilityai/stable-diffusion-2-1'

Data: 3300 midjourney 5.1 upscaled images with their captions. # Training parameters

Duration: 4000 steps
LR scheduler: polynomial
Batch size: 3
Text encoder: Thawed
Optimizer: 8bit ADAM
No prior loss preservation