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--- |
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library_name: transformers |
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license: apache-2.0 |
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datasets: |
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- Gustavosta/Stable-Diffusion-Prompts |
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language: |
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- en |
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tags: |
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- completion |
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inference: |
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parameters: |
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max_new_tokens: 20 |
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do_sample: True |
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temperature: 2.0 |
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num_beams: 10 |
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repetition_penalty: 1.2 |
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top_k: 40 |
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top_p: 0.75 |
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--- |
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# MagicPrompt TinyStories-33M (Merged) |
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## Info |
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Magic prompt completion model trained on a dataset 70k Stable Diffusion prompts. Base model: TinyStories-33M. Inspired by [MagicPrompt-Stable-Diffusion](Gustavosta/MagicPrompt-Stable-Diffusion). |
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Model seems to be pretty decent for 33M params, but it clearly lacks much of an understanding of pretty much anything. Still, considering the size, I think it's decent. Whether you would use this over a small GPT-2 based model is up to you. |
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## Examples |
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Generation settings: `max_new_tokens=40, do_sample=True, temperature=2.0, num_beams=10, repetition_penalty=1.2, top_k=40, top_p=0.75, eos_token_id=tokenizer.eos_token_id` (there may be better settings). |
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(Bold text is generated by the model) |
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"A close shot of a bird in a jungle, **with two legs, with long hair on a tall, long brown body, long white skin, sharp teeth, high bones, digital painting, artstation, concept art, illustration by wlop,**" |
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"Camera shot of **a strange young girl wearing a cloak, wearing a mask in clothes, with long curly hair, long hair, black eyes, dark skin, white teeth, long brown eyes eyes, big eyes, sharp**" |
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"An illustration of a house, stormy weather, **sun, moonlight, night, concept art, 4 k, wlop, by wlop, by jose stanley, ilya kuvshinov, sprig**" |
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"A field of flowers, camera shot, 70mm lens, **fantasy, intricate, highly detailed, artstation, concept art, sharp focus, illustration, illustration, artgerm jake daggaws, artgerm and jaggodieie brad**" |
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## Training config |
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- Rank 16 LoRA |
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- Trained on Gustavosta/Stable-Diffusion-Prompts for 10 epochs |
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- Batch size of 64 |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- load_in_8bit: False |
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- load_in_4bit: True |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: fp4 |
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- bnb_4bit_use_double_quant: False |
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- bnb_4bit_compute_dtype: float32 |
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### Framework versions |
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- PEFT 0.5.0.dev0 |
