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README.md

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+---
+library_name: transformers
+base_model: unsloth/gemma-3-270m
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- gemma3_text
+- trl
+license: gemma
+---
+
+# PromptTuner v0.1
+
+**PromptTuner-v0.1** is a fine-tuned [gemma-3-270M-it](https://huggingface.co/google/gemma-3-270m-it) model specifically designed to enhance text prompts for text-to-image models. 
+
+This model takes a basic image concept and expands into rich, detailed descriptions including:
+- Visual composition and perspective
+- Artistic style and medium
+- Color palette and lighting
+- Atmosphere and mood
+- Textures and materials
+- Environmental context
+
+The model tries preserves the core intent of your original prompt while adding professional-quality visual descriptors.
+
+## Dataset
+
+The model was trained on a curated collection of prompt/magic-prompt pairs. 
+
+The dataset underwent extensive cleaning to ensure quality:
+- Removed duplicates
+- Removed prompts consisting only of numbers and spaces
+- Filtered out magic prompts containing error messages or refusal responses
+- Removed magic prompts below quality thresholds
+- Cleaned up quotation marks at prompt boundaries
+- Removed rows with excessively short prompts (length <= 2)
+- Filtered out web links and URLs
+- Removed gibberish inputs
+- Filtered pairs where prompt and magic prompt were too similar
+
+The training dataset was balanced using K-means clustering on prompt embeddings to ensure diverse representation of creative concepts.
+
+## Training
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://api.wandb.ai/links/shb777-self/ugs1nrkm) 
+
+- **Training Method**: LoRA
+  - Rank: 16
+  - Alpha: 32
+  - Target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+- **Epochs**: 3
+- **Batch Size**: 16
+- **Learning Rate**: 2e-4
+- **Optimizer**: adamw_8bit
+- **LR Scheduler**: Cosine
+- **Warmup Ratio**: 0.1
+- **Train/Test Split**: 90/10
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained("shb777/PromptTuner-v0.1")
+tokenizer = AutoTokenizer.from_pretrained("shb777/PromptTuner-v0.1")
+
+SYSTEM_PROMPT = """You are an expert creative director specializing in visual descriptions for image generation.
+
+Your task: Transform the user's concept into a rich, detailed image description while PRESERVING their core idea.
+
+IMPORTANT RULES:
+1. Keep ALL key elements (intents, entities) from the original concept
+2. Enhance with artistic details, NOT change the fundamental idea
+3. Maintain the user's intended subject, action, and setting
+
+You should elaborate on:
+- Visual composition and perspective
+- Artistic style (photorealistic, impressionist, etc.)
+- Color palette and color temperature
+- Lighting (golden hour, dramatic shadows, etc.)
+- Atmosphere and mood
+- Textures and materials
+- Technical details (medium, brushwork, rendering style)
+- Environmental context (time of day, weather, season, era)
+- Level of detail and focus points
+
+Output format: A single, flowing paragraph that reads naturally as an image prompt."""
+
+user_input = "fox, red tail, blue moon, clouds"
+
+messages = [
+    {"role": "system", "content": SYSTEM_PROMPT},
+    {"role": "user", "content": user_input}
+]
+
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(prompt, return_tensors="pt")
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=512,
+    temperature=1.0,
+    top_p=0.95,
+    top_k=64
+)
+
+enhanced_prompt = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(enhanced_prompt)
+```
+
+### Recommended Generation Parameters
+
+> [!NOTE]
+> You must use the exact system prompt shown above, as the model was trained on it. 
+
+- `max_new_tokens`: 512
+- `temperature`: 1.0
+- `top_p`: 0.95
+- `top_k`: 64
+
+You can try the model directly at [TinkerSpace](https://huggingface.co/spaces/shb777/TinkerSpace) HF Space.
+
+## Limitations
+
+This is only the first version of PromptTuner. As an initial release, the model may:
+- Occasionally lose details and relationships from multi-entity prompts
+- Sometimes introduce stylistic elements and text not present in the original concept
+
+Feedback and suggestions for improvement are welcome.
+
+## License
+
+This model is built upon Google's Gemma 3. Please refer to the Gemma license for usage terms.
+
+## Citation
+
+If you use this model in your work, please cite:
+
+```bibtex
+@model{prompt_tuner_v0.1,
+  title={PromptTuner-v0.1: A Fine-tuned Gemma3-270M for Prompt Enhancement},
+  author={shb777},
+  year={2025},
+  url={https://huggingface.co/shb777/PromptTuner-v0.1}
+}
+```
+
+## Acknowledgments
+
+- Base model: [google/gemma-3-270M-it](https://huggingface.co/google/gemma-3-270M-it)
+- Training framework: [Unsloth](https://github.com/unslothai/unsloth)

added_tokens.json

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+{
+  "<image_soft_token>": 262144
+}

chat_template.jinja

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+{# Unsloth Chat template fixes #}
+
+{%- if messages[0]['role'] == 'system' -%}
+    {%- if messages[0]['content'] is string -%}
+        {%- set first_user_prefix = messages[0]['content'] + '
+
+' -%}
+    {%- else -%}
+        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
+
+' -%}
+    {%- endif -%}
+    {%- set loop_messages = messages[1:] -%}
+{%- else -%}
+    {%- set first_user_prefix = "" -%}
+    {%- set loop_messages = messages -%}
+{%- endif -%}
+{%- for message in loop_messages -%}
+    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
+        {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
+    {%- endif -%}
+    {%- if (message['role'] == 'assistant') -%}
+        {%- set role = "model" -%}
+    {%- else -%}
+        {%- set role = message['role'] -%}
+    {%- endif -%}
+    {{ '<start_of_turn>' + role + '
+' + (first_user_prefix if loop.first else "") }}
+    {%- if message['content'] is string -%}
+        {{ message['content'] | trim }}
+    {%- elif message['content'] is iterable -%}
+        {%- for item in message['content'] -%}
+            {%- if item['type'] == 'image' -%}
+                {{ '<start_of_image>' }}
+            {%- elif item['type'] == 'text' -%}
+                {{ item['text'] | trim }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- elif message['content'] is defined -%}
+        {{ raise_exception("Invalid content type") }}
+    {%- endif -%}
+    {{ '<end_of_turn>
+' }}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{'<start_of_turn>model
+'}}
+{%- endif -%}
+
+{# Copyright 2025-present Unsloth. Apache 2.0 License. #}

config.json

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+{
+  "_sliding_window_pattern": 6,
+  "architectures": [
+    "Gemma3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": null,
+  "bos_token_id": 2,
+  "dtype": "bfloat16",
+  "eos_token_id": 106,
+  "final_logit_softcapping": null,
+  "head_dim": 256,
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 640,
+  "initializer_range": 0.02,
+  "intermediate_size": 2048,
+  "layer_types": [
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "model_type": "gemma3_text",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 18,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_local_base_freq": 10000.0,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": 512,
+  "transformers_version": "4.57.3",
+  "unsloth_fixed": true,
+  "unsloth_version": "2025.12.9",
+  "use_bidirectional_attention": false,
+  "use_cache": true,
+  "vocab_size": 262144
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "eos_token_id": 106,
+  "max_length": 32768,
+  "pad_token_id": 0,
+  "transformers_version": "4.57.3"
+}

model.safetensors

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+oid sha256:d749f35a81ff0884023bb2b74f1441f1c0c870e1fa41054d603c9da4a566201d
+size 536334056

special_tokens_map.json

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+{
+  "boi_token": "<start_of_image>",
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eoi_token": "<end_of_image>",
+  "eos_token": {
+    "content": "<end_of_turn>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "image_token": "<image_soft_token>",
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
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+size 33384568