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Model: aifeifei798/Qwen3-1.7B-Flux-Prompt Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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tags:
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- qwen
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- qwen3
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- unsloth
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- decision-making
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- strategic-analysis
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- cognitive-architecture
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- chat
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- philosophy-driven-ai
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pipeline_tag: text-generation
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base_model:
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- Qwen/Qwen3-1.7B
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datasets:
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- ABDALLALSWAITI/flux_prompt
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---
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---
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### Thanks mradermacher: For creating the GGUF versions of these models
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https://huggingface.co/mradermacher/Qwen3-1.7B-Flux-Prompt-GGUF
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https://huggingface.co/mradermacher/Qwen3-1.7B-Flux-Prompt-i1-GGUF
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---
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# Qwen3-1.7B-Flux-Prompt
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**Turn simple words into professional Flux.1 image prompts instantly.**
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This is a fine-tuned version of **Qwen3-1.7B-Instruct**, specialized in expanding short concepts into detailed, high-quality descriptions optimized for **Flux.1** image generation models.
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## ✨ Key Features
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* **🚀 Lightweight & Fast**: Based on the 1.7B model, it runs extremely fast even on older GPUs or CPU.
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* **🧠 "Invisible" System Prompt**: The specialized system prompt is **baked into the `tokenizer_config.json`**. You don't need to type complex instructions. Just input `a cat`, and it outputs the full prompt automatically.
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* **🎨 Non-Conversational**: It doesn't chat. It doesn't say "Here is your prompt". It only outputs the raw prompt, ready for your stable diffusion pipeline.
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* **✅ Validated Quality**: Tested thoroughly for diversity and detail (see examples below).
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---
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## 🖼️ Examples
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**Input:** `a sexy model at home bed`
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**Output (Generated by this model):**
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> a sexy model at home bed, close-up shot of a woman lying on a luxurious velvet bed with soft golden lighting, elegant floral decor, minimalist modern furniture, subtle candlelight flicker, realistic textures, sensual atmosphere, high-quality photography, dramatic shadows, and a calm yet intimate mood.
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---
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## 💻 How to Use
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### Method 1: Python (Transformers)
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Since the system prompt is integrated, the usage is extremely simple:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_name = "aifeifei798/Qwen3-1.7B-Flux-Prompt" # Replace with your actual repo name
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# Load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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def generate_flux_prompt(prompt):
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messages = [{"role": "user", "content": prompt}]
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# Applying the template
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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# enable_thinking=False
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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# Generation with optimized parameters for Flux prompting
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=512, # [Key] 512 tokens are sufficient for a detailed visual description.
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do_sample=True, # [Required] Enable sampling to allow for creative variations.
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temperature=0.7, # [Creativity] 0.7 offers a balance between imaginative detail and coherence.
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top_p=0.9, # [Focus] Nucleus sampling: filters out very unlikely words.
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top_k=50, # [Stability] Limits vocabulary to top 50 tokens to prevent hallucinations.
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repetition_penalty=1.15, # [Variety] Slight penalty to reduce repetitive phrases without breaking grammar.
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no_repeat_ngram_size=3,
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)
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# Extracting the newly generated tokens only
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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# Parsing logic to handle potential reasoning content (if using a reasoning-capable base model)
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# Looks for the </think> token ID (usually 151668 in Qwen architecture)
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try:
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index = len(output_ids) - output_ids[::-1].index(151668)
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except ValueError:
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index = 0 # No thinking trace found, output starts from the beginning
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# Decode the final prompt
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# thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip()
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content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip()
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return content
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# Example Usage
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# if __name__ == "__main__":
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# user_input = "a sexy model at new york"
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# print(f"Input: {user_input}\n")
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# print(f"Generated Flux Prompt:\n{generate_flux_prompt(user_input)}")
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```
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---
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## 🔧 Training Details
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* **Base Model:** Qwen/Qwen3-1.7B-Instruct
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* **Dataset:** `flux_prompt` (Alpaca format)
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* **Fine-tuning Framework:** Unsloth
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* **Configuration:**
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* `temperature`: 0.7 (Recommended)
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* `repetition_penalty`: 1.05 - 1.1 (Recommended)
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---
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### 💡 Tips for Users
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* **Keep it Simple:** The model thrives on simple inputs like "a girl in rain" or "futuristic car".
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* **Sampling:** Always use `do_sample=True` with `temperature` around 0.7 to get diverse results every time you run it.
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added_tokens.json
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{
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"</think>": 151668,
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"</tool_response>": 151666,
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"<|endoftext|>": 151643,
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"<|fim_middle|>": 151660,
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"<|im_end|>": 151645,
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"<|quad_end|>": 151651,
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"<|repo_name|>": 151663,
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}
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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"dtype": "bfloat16",
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 6144,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 40960,
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"max_window_layers": 28,
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"model_type": "qwen3",
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"num_attention_heads": 16,
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"num_hidden_layers": 28,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000,
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"tie_word_embeddings": true,
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"transformers_version": "4.57.1",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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{
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"top_p": 0.95,
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"transformers_version": "4.57.1"
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}
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
240
tokenizer_config.json
Normal file
240
tokenizer_config.json
Normal file
@@ -0,0 +1,240 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- set flux_system_prompt = \"You are an AI assistant specialized in generating high-quality prompts for Flux image generation. Output the prompt ONLY. Do not output any introduction or conversational text.\" %}{{- '<|im_start|>system\\n' + flux_system_prompt + '<|im_end|>\\n' }}{%- for message in messages %}{%- if message.role == \"system\" and loop.first %}{# Skip the first system message from input because we forced the Flux prompt at the top #}{%- else %}{{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>\\n' }}{%- endif %}{%- endfor %}{%- if add_generation_prompt %}{{- '<|im_start|>assistant\\n' }}{%- endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user