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Model: FutureMa/Qwen3-8B-Drama-Thinking Source: Original Platform
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---
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license: apache-2.0
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base_model: Qwen/Qwen3-8B
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tags:
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- qwen3
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- thinking
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- creative-writing
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- screenwriting
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- drama
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- chain-of-thought
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- reasoning
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- ms-swift
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- full-parameter-finetuning
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datasets:
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- custom-drama-thinking-dataset
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language:
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- en
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- zh
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library_name: transformers
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pipeline_tag: text-generation
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model-index:
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- name: Qwen3-8B-Drama-Thinking
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results:
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- task:
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type: text-generation
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name: Creative Script Writing
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metrics:
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- type: thinking_depth
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value: 9.0
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name: Thinking Depth Score
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- type: script_format
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value: 9.0
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name: Script Format Score
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- type: dramatic_craft
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value: 8.5
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name: Dramatic Craft Score
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---
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# Qwen3-8B-Drama-Thinking
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This model is a **full parameter fine-tuned** version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on a custom drama thinking dataset with explicit creative reasoning chains.
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## Model Description
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- **Base Model**: Qwen3-8B (8 billion parameters)
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- **Training Method**: Full Parameter Fine-tuning (NOT LoRA)
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- **Training Framework**: [ms-swift](https://github.com/modelscope/ms-swift)
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- **Training Data**: Custom Drama Thinking Dataset (6,319 samples, avg ~5,000 tokens)
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- **Specialization**: Screenwriting with explicit `<think>...</think>` creative reasoning
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- **Hardware**: 2x NVIDIA H100 80GB SXM5
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- **Training Time**: 2 hours 46 minutes (3 epochs)
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- **Training Cost**: ~$17.86
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## Key Features
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### 🎬 Professional Screenwriting Assistant
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This model generates dramatic scripts with **explicit creative deliberation**:
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- ✅ **Thinking Process Visible**: Uses `<think>...</think>` tags to show internal reasoning
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- ✅ **Deep Character Psychology**: Analyzes motivations, defense mechanisms, subtext
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- ✅ **Structural Planning**: Three-act structure, emotional arcs, pacing decisions
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- ✅ **Visual Storytelling**: Symbolism, atmosphere, cinematographic choices
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- ✅ **Professional Format**: Correct screenplay formatting (scene headers, action lines, dialogue)
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### 📊 Performance Comparison
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Compared to base Qwen3-8B:
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| Metric | Base Model | Fine-Tuned | Improvement |
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|--------|------------|------------|-------------|
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| **Output Length** | 1,071 tokens | 3,874 tokens | **+262%** |
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| **Thinking Depth** | 5/10 | 9/10 | **+80%** |
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| **Creative Reasoning** | 500 tokens | 3,400 tokens | **+580%** |
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| **Craft Analysis** | Generic | Professional | **Qualitative leap** |
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### 🎯 Unique Value Proposition
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> This is not just a text generator - it's a **creative thinking partner** that externalizes
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> the entire screenwriting process: from title analysis to character psychology to structural
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> planning to final execution.
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## Training Details
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### Training Configuration
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```bash
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Model: Qwen/Qwen3-8B
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Template: qwen3_thinking
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Training Type: Full Parameter (all 8B parameters)
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Max Length: 8192 tokens (for long thinking chains)
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Batch Size: 1 per device × 2 GPUs
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Gradient Accum: 8 steps (effective batch size: 16)
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Learning Rate: 1e-5
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Epochs: 3
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Optimization: DeepSpeed Zero3 + Gradient Checkpointing
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Liger Kernel, BF16 mixed precision
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Loss Scale: ignore_empty_think
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GPU Memory: ~74.62 GB per H100 (stable)
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```
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### Dataset Characteristics
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- **Samples**: 6,319 dramatic script continuations
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- **Average Length**: ~5,000 tokens per sample
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- **Max Length**: ~6,100 tokens
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- **Format**: Conversations with `<think>...</think>` reasoning tags
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- **Content**:
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- Script opening scenes (title, description, initial dialogue)
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- Extensive creative deliberation (3,000+ tokens of thinking)
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- Script continuation with proper formatting
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- **Style**: Dramatic, emotionally intense scenarios (conflicts, reconciliation, tragedy)
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### Training Metrics
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- **Final Loss**: 0.844
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- **Average Loss**: 0.978
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- **Loss Trajectory**: 1.602 (start) → 0.82-0.83 (end)
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- **Training Speed**: ~8 seconds/iteration
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- **Total Steps**: 1,185
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- **Checkpoints**: 5 saved (400, 800, 900, 1000, 1185)
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## Usage
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### Quick Start (ms-swift)
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```bash
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# Install ms-swift
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pip install ms-swift
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# Inference (interactive mode)
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swift infer \
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--ckpt_dir FutureMa/Qwen3-8B-Drama-Thinking \
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--template qwen3_thinking \
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--max_new_tokens 4096 \
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--temperature 0.7
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```
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### Python API
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```python
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import os
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os.environ['CUDA_VISIBLE_DEVICES'] = '0'
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from swift.llm import PtEngine, InferRequest, RequestConfig
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# Initialize engine
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engine = PtEngine(
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model_id_or_path="FutureMa/Qwen3-8B-Drama-Thinking",
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max_batch_size=1,
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torch_dtype="bfloat16"
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)
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# Create prompt
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prompt = """Title: The Reunion
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Description: Two estranged siblings meet at their childhood home after 20 years.
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INT. FAMILY LIVING ROOM - DAY
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SARAH (35) stands by the window, looking out at the garden.
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MICHAEL (38) enters, hesitant."""
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# Generate (streaming)
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messages = [{'role': 'user', 'content': prompt}]
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request = InferRequest(messages=messages)
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config = RequestConfig(max_tokens=4096, temperature=0.7, stream=True)
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for response in engine.infer([request], config)[0]:
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if response:
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print(response.choices[0].delta.content, end='', flush=True)
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```
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### Using with Transformers (requires adapting checkpoint)
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained(
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"FutureMa/Qwen3-8B-Drama-Thinking",
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torch_dtype="bfloat16",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B")
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messages = [
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{"role": "system", "content": "You are a creative screenwriter assistant specialized in dramatic storytelling with internal reasoning."},
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{"role": "user", "content": "Write a scene about forgiveness..."}
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]
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text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer([text], return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=4096, temperature=0.7)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## Example Output
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**Input Prompt:**
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```
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Title: The Last Apology
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Description: A daughter arrives at her estranged father's deathbed...
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```
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**Model Output** (excerpt):
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```
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<think>
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Okay. Let's go. I'm sitting here with the opening of *The Last Apology* fresh in my mind,
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and I need to figure out exactly where this goes next—not just the next scene, but the next
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emotional beat, the next structural pivot...
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First, the title: *The Last Apology*. That's not just poetic—it's structural. It tells me
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this story is about delayed recognition, about the finality of words left unsaid...
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[3,400 tokens of deep creative analysis including:]
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- Title deconstruction and thematic implications
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- Character psychology analysis
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- Three-act structure planning
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- Visual language and symbolism
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- Multiple narrative paths considered
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- Professional screenwriting techniques
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</think>
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INT. HOSPITAL ROOM - NIGHT
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ANNA (28), in a wrinkled business suit, hesitates at the doorway.
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DAVID (65) lies in bed, breathing labored...
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[Script continues with proper formatting]
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```
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## Intended Use
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### ✅ Recommended Use Cases
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1. **Screenwriting Education**: Learn professional creative thinking process
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2. **Script Ideation**: Generate story frameworks and narrative alternatives
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3. **Story Consulting**: Explore "what if" scenarios with explicit reasoning
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4. **Creative Brainstorming**: Understand decision-making in storytelling
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5. **Draft Development**: Plan structure before execution
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### ❌ Not Recommended For
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1. **Final Shooting Scripts**: Requires human refinement for production
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2. **Comedy/Action Genres**: Training bias toward dramatic content
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3. **Long-form Series**: Single-pass generation may lack consistency
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4. **Immediate Production**: Dialogue needs naturalization
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## Evaluation Results
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### Quantitative Metrics (vs. Base Model)
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| Aspect | Score | Base Model | Improvement |
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|--------|-------|------------|-------------|
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| **Thinking Depth** | 9/10 | 5/10 | +80% |
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| **Script Format** | 9/10 | 8/10 | +13% |
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| **Dramatic Craft** | 8.5/10 | 8/10 | +6% |
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| **Character Psychology** | 9/10 | 6/10 | +50% |
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| **Decision Transparency** | 9/10 | 5/10 | +80% |
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| **Overall** | 8.1/10 | 6.9/10 | +17% |
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> **Note on Methodology:**
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> *These metrics are generated using an **LLM-as-a-Judge** framework (Claude) comparing the fine-tuned model against the base model.
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### Qualitative Improvements
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- ✅ **Professional Voice**: Sounds like experienced screenwriter
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- ✅ **Structural Thinking**: Explicit three-act planning
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- ✅ **Meta-Awareness**: "This isn't just a script. It's a reckoning."
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- ✅ **Non-Linear Reasoning**: Considers alternatives, backtracks, refines
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- ✅ **Craft-Oriented**: Explains why choices serve the story
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## Limitations
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1. **Thinking Verbosity**: Generates ~3,400 tokens of thinking (87% of output)
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- May be excessive for quick tasks
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- Consider using `max_new_tokens` to limit length
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2. **Incomplete Execution**: Token budget consumed by thinking
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- Many planned scenes not fully generated
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- May need 6,000-8,000 token limit for complete scripts
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3. **Dialogue Naturalness**: More direct/literary than conversational
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- Training data style influences output
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- May need post-processing for natural speech
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4. **Training Data Bias**: Skews toward melodramatic scenarios
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- Less suited for subtle/realistic dialogue
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- Best for emotionally intense stories
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## Training Insights
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### What Made This Successful
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1. **8192 Token Context**: Essential for capturing full thinking chains
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- Initial assumption of 2048 would have truncated data
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- Average sample length: ~5,000 tokens
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2. **DeepSpeed Zero3**: Required (not optional)
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- Single H100: Would need ~109-114 GB (OOM)
|
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- Zero3 sharding: ~74.62 GB per card ✅
|
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3. **Full Parameter Training**: Worth the cost
|
||||
- Deeper capability transfer than LoRA
|
||||
- Better thinking process internalization
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- Cost: $17.86 (2.8 hours) vs ~$5 for LoRA
|
||||
|
||||
4. **Quality Training Data**: 6,319 long-form reasoning examples
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- Actual creative process in `<think>` tags
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- High-quality dramatic writing
|
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## Citation
|
||||
|
||||
```bibtex
|
||||
@misc{qwen3-drama-thinking-2025,
|
||||
author = {FutureMa},
|
||||
title = {Qwen3-8B-Drama-Thinking: Full Parameter Fine-tuning for Creative Screenwriting},
|
||||
year = {2025},
|
||||
publisher = {HuggingFace},
|
||||
howpublished = {\url{https://huggingface.co/FutureMa/Qwen3-8B-Drama-Thinking}},
|
||||
note = {Full parameter fine-tuning on 6,319 drama samples with explicit reasoning chains}
|
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}
|
||||
```
|
||||
|
||||
## News & Updates
|
||||
|
||||
**[2025-12-23]** 🎉 **DramaBench Dataset is now open-source!** Evaluate your drama script generation with our comprehensive 6-dimensional benchmark framework (Format Standards, Narrative Efficiency, Character Consistency, Emotional Depth, Logic Consistency, Conflict Handling).
|
||||
- 📊 Dataset: [FutureMa/DramaBench](https://huggingface.co/datasets/FutureMa/DramaBench)
|
||||
- 📄 Paper: [arXiv:2512.19012](https://arxiv.org/abs/2512.19012)
|
||||
- 🌐 Demo: [dramabench.pages.dev](https://dramabench.pages.dev/)
|
||||
|
||||
---
|
||||
|
||||
## Acknowledgments
|
||||
|
||||
- **Base Model**: [Qwen Team](https://huggingface.co/Qwen) - Qwen3-8B
|
||||
- **Training Framework**: [ms-swift](https://github.com/modelscope/ms-swift) - ModelScope SWIFT
|
||||
- **Infrastructure**: [Lambda Cloud](https://lambdalabs.com/) - 2x H100 80GB SXM5
|
||||
- **Dataset**: Custom Drama Thinking Dataset (6,319 samples)
|
||||
|
||||
## Model Card Contact
|
||||
|
||||
For questions or feedback:
|
||||
- **HuggingFace**: [@FutureMa](https://huggingface.co/FutureMa)
|
||||
- **GitHub Issues**: Report via ms-swift repository
|
||||
|
||||
---
|
||||
|
||||
**Training Date**: 2025-12-08
|
||||
**Training Duration**: 2h 46m
|
||||
**Model Size**: ~16GB (BF16 precision)
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**Recommended VRAM**: 16GB+ for inference
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28
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|
||||
"<|vision_end|>": 151653,
|
||||
"<|vision_pad|>": 151654,
|
||||
"<|vision_start|>": 151652
|
||||
}
|
||||
89
chat_template.jinja
Normal file
89
chat_template.jinja
Normal file
@@ -0,0 +1,89 @@
|
||||
{%- if tools %}
|
||||
{{- '<|im_start|>system\n' }}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- messages[0].content + '\n\n' }}
|
||||
{%- endif %}
|
||||
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||
{%- for tool in tools %}
|
||||
{{- "\n" }}
|
||||
{{- tool | tojson }}
|
||||
{%- endfor %}
|
||||
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||
{%- else %}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
||||
{%- for message in messages[::-1] %}
|
||||
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||
{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
|
||||
{%- set ns.multi_step_tool = false %}
|
||||
{%- set ns.last_query_index = index %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- for message in messages %}
|
||||
{%- if message.content is string %}
|
||||
{%- set content = message.content %}
|
||||
{%- else %}
|
||||
{%- set content = '' %}
|
||||
{%- endif %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{%- set reasoning_content = '' %}
|
||||
{%- if message.reasoning_content is string %}
|
||||
{%- set reasoning_content = message.reasoning_content %}
|
||||
{%- else %}
|
||||
{%- if '</think>' in content %}
|
||||
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
||||
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- if loop.index0 > ns.last_query_index %}
|
||||
{%- if loop.last or (not loop.last and reasoning_content) %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- if enable_thinking is defined and enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
68
config.json
Normal file
68
config.json
Normal file
@@ -0,0 +1,68 @@
|
||||
{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"dtype": "bfloat16",
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 4096,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 12288,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 40960,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": 151643,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": false,
|
||||
"transformers_version": "4.57.3",
|
||||
"use_cache": false,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||
13
generation_config.json
Normal file
13
generation_config.json
Normal file
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"temperature": 0.6,
|
||||
"top_k": 20,
|
||||
"top_p": 0.95,
|
||||
"transformers_version": "4.57.3"
|
||||
}
|
||||
BIN
merges.txt
(Stored with Git LFS)
Normal file
BIN
merges.txt
(Stored with Git LFS)
Normal file
Binary file not shown.
3
model-00001-of-00004.safetensors
Normal file
3
model-00001-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:5f60e26ff9187a86191977fe255865508da9ba5d8f84c7181b76673a38c32fa9
|
||||
size 4902257696
|
||||
3
model-00002-of-00004.safetensors
Normal file
3
model-00002-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:372cc2f41d3805d0976cb2c4235ffced77133720f0cef420eacb1d3f975e9c13
|
||||
size 4915960368
|
||||
3
model-00003-of-00004.safetensors
Normal file
3
model-00003-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:c5d4596e6ad0c9c053e7e3a7f9efb1b55c1d48c9fea8a3719beb328af0df58b2
|
||||
size 4983068496
|
||||
3
model-00004-of-00004.safetensors
Normal file
3
model-00004-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3acb42d50dbac0844e4f237dfe285ef618b93468fbe3d541c7f65d9dbc72ae5a
|
||||
size 1580230264
|
||||
407
model.safetensors.index.json
Normal file
407
model.safetensors.index.json
Normal file
@@ -0,0 +1,407 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_parameters": 308224,
|
||||
"total_size": 16381470720
|
||||
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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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|
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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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|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
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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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|
||||
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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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|
||||
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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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|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
239
tokenizer_config.json
Normal file
239
tokenizer_config.json
Normal file
@@ -0,0 +1,239 @@
|
||||
{
|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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|
||||
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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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||||
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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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|
||||
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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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|
||||
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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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||||
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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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|
||||
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|
||||
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|
||||
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|
||||
"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,
|
||||
"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
|
||||
}
|
||||
1700
trainer_state.json
Normal file
1700
trainer_state.json
Normal file
File diff suppressed because it is too large
Load Diff
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:d02cf2a49c614bff625160d51a72e2126e582e1938773da64ec29b678ba890ae
|
||||
size 9553
|
||||
BIN
vocab.json
(Stored with Git LFS)
Normal file
BIN
vocab.json
(Stored with Git LFS)
Normal file
Binary file not shown.
Reference in New Issue
Block a user