|
--- |
|
license: bigscience-bloom-rail-1.0 |
|
tags: |
|
- generated_from_trainer |
|
- stable-diffusion |
|
- diffusion |
|
model-index: |
|
- name: bloom-560m-finetuned-sd-prompts |
|
results: [] |
|
|
|
datasets: |
|
- Gustavosta/Stable-Diffusion-Prompts |
|
|
|
widget: |
|
- text: "<s>Prompt: young, curly haired, redhead Natalie Portman as a" |
|
- text: "<s>Prompt: a powerful energy woman, by alexander fedosav" |
|
|
|
inference: |
|
parameters: |
|
eos_token_id: 2 |
|
max_length: 128 |
|
|
|
|
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# bloom-560m-finetuned-sd-prompts |
|
|
|
This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the [Gustavosta/Stable-Diffusion-Prompts](https://huggingface.co/datasets/Gustavosta/Stable-Diffusion-Prompts) dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8742 |
|
|
|
|
|
## Example of usage |
|
|
|
```py |
|
import torch |
|
from transformers import BloomTokenizerFast, BloomForCausalLM |
|
|
|
device = 'cuda' if torch.cuda.is_available() else 'cpu' |
|
ckpt = 'mrm8488/bloom-560m-finetuned-sd-prompts' |
|
|
|
tokenizer = BloomTokenizerFast.from_pretrained(ckpt) |
|
model = BloomForCausalLM.from_pretrained(ckpt).to(device) |
|
|
|
def generate_prompt(text): |
|
inputs = tokenizer(text, return_tensors='pt') |
|
input_ids = inputs.input_ids.to(device) |
|
attention_mask = inputs.attention_mask.to(device) |
|
output = model.generate(input_ids, attention_mask=attention_mask, repetition_penalty=1.05, max_length=2048, eos_token_id=tokenizer.eos_token_id) |
|
|
|
return tokenizer.decode(output[0], skip_special_tokens=False) |
|
|
|
text = "<s>Prompt: pikachu dinning in the eiffel tower" |
|
|
|
generate_prompt(text) |
|
|
|
# Output: <s>Prompt: pikachu dinning in the eiffel tower, intricate, elegant, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha</s> |
|
``` |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 5e-05 |
|
- train_batch_size: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 4 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 2 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 2.6743 | 0.17 | 100 | 2.0891 | |
|
| 1.8919 | 0.33 | 200 | 1.7191 | |
|
| 1.5907 | 0.5 | 300 | 1.4454 | |
|
| 1.3865 | 0.67 | 400 | 1.3247 | |
|
| 1.2487 | 0.83 | 500 | 1.2150 | |
|
| 1.1565 | 1.0 | 600 | 1.1031 | |
|
| 0.896 | 1.17 | 700 | 1.0612 | |
|
| 0.8389 | 1.33 | 800 | 0.9994 | |
|
| 0.8071 | 1.5 | 900 | 0.9530 | |
|
| 0.7628 | 1.67 | 1000 | 0.9206 | |
|
| 0.7423 | 1.83 | 1100 | 0.8883 | |
|
| 0.7155 | 2.0 | 1200 | 0.8742 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.22.1 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.5.1 |
|
- Tokenizers 0.12.1 |
|
|
