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Model: jaigouk/qwen3-4b-german-teacher-v1 Source: Original Platform
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---
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license: apache-2.0
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base_model: Qwen/Qwen3-4B
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tags:
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- german
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- language-learning
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- grammar
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- education
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- qwen3
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- finetuned
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- sft
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language:
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- de
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- en
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pipeline_tag: text-generation
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library_name: transformers
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datasets:
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- custom
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model-index:
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- name: qwen3-4b-german-teacher
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results:
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- task:
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type: text-generation
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name: German Grammar Teaching
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metrics:
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- type: cola_mcc
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value: 0.721
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name: CoLA MCC (Grammaticality Judgment)
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- type: gec_f1
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value: 0.349
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name: GEC Macro F1 (Error Correction)
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- type: generation_quality
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value: 3.99
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name: Generation Quality (1-5 scale)
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- type: overall_score
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value: 0.633
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name: Overall Score
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---
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# Qwen3-4B German Teacher
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A finetuned [Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) model specialized for German language teaching at A1-B1 CEFR levels. This model excels at:
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- **Grammar Error Detection**: Identifying grammatical mistakes in German sentences
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- **Error Correction**: Providing correct forms with clear explanations
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- **Grammar Judgment**: Binary classification of sentence grammaticality (CoLA-style)
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- **Teaching Explanations**: Clear, learner-friendly explanations of German grammar rules
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## Model Details
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| Property | Value |
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|----------|-------|
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| Base Model | Qwen/Qwen3-4B |
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| Parameters | 4B |
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| Training Method | SFT (Supervised Fine-Tuning) with LoRA |
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| LoRA Rank | 32 |
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| LoRA Alpha | 64 |
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| Training Epochs | 2 |
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| Learning Rate | 2e-4 |
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| Context Length | 4096 tokens |
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## Performance
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Evaluated on a custom German grammar benchmark:
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| Metric | Score | Description |
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|--------|-------|-------------|
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| **CoLA MCC** | 0.721 | Matthews Correlation Coefficient for grammaticality judgment |
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| **GEC F1** | 0.349 | Macro F1 for grammar error correction |
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| **Generation Quality** | 3.99/5.0 | Human-evaluated response quality |
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| **Overall Score** | 0.633 | Weighted composite score |
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### Benchmark Comparison
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Comparison with SmolLM3-German-V6 (3B parameters, Q4 quantized):
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| Metric | Qwen3 German Teacher (4B) | SmolLM3-German-V6 (3B) | Improvement |
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|--------|---------------------------|------------------------|-------------|
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| **CoLA MCC** | **0.721** | 0.624 | +15.5% |
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| **GEC F1** | **0.349** | 0.145 | +140.7% |
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| **Generation Quality** | **3.99** | 3.19 | +25.1% |
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| **Overall Score** | **0.633** | 0.492 | +28.7% |
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Key advantages of this model:
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- **Superior grammaticality judgment**: 15.5% higher CoLA MCC score
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- **Much better error correction**: 2.4x better GEC F1 score
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- **Higher quality responses**: 0.8 points higher on 5-point scale
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## Training Data
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The model was trained on ~9,000 examples with the following composition:
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| Category | Percentage | Purpose |
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|----------|------------|---------|
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| Grammar Correction | 35% | Error correction patterns |
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| Grammar Judgment | 25% | CoLA-style "Is this correct?" examples |
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| Structured Teaching | 20% | Verb conjugations, grammar explanations |
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| General Conversation | 20% | Fluency preservation |
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### Key Training Focus Areas
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- **haben/sein auxiliary verbs**: Movement verbs require "sein" (e.g., "Ich bin gefahren" not "Ich habe gefahren")
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- **Article gender** (der/die/das)
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- **Case usage** (Nominativ, Akkusativ, Dativ, Genitiv)
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- **Word order** in German sentences
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## Usage
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### With Transformers
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("jaigouk/qwen3-4b-german-teacher")
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tokenizer = AutoTokenizer.from_pretrained("jaigouk/qwen3-4b-german-teacher")
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messages = [
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{"role": "system", "content": "Du bist ein freundlicher Deutschlehrer für A1-B1 Lernende."},
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{"role": "user", "content": "Is this German sentence correct? 'Ich habe nach Berlin gefahren.'"}
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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")
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outputs = model.generate(**inputs, max_new_tokens=256)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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### With Ollama (GGUF)
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1. Download the GGUF file: `qwen3-german-teacher-Q4_K_M.gguf`
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2. Create a Modelfile:
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```dockerfile
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FROM ./qwen3-german-teacher-Q4_K_M.gguf
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TEMPLATE """{{- if .System }}<|im_start|>system
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{{ .System }}<|im_end|>
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{{ end }}<|im_start|>user
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{{ .Prompt }}<|im_end|>
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<|im_start|>assistant
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<think>
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</think>
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{{ .Response }}<|im_end|>
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"""
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PARAMETER stop "<|im_end|>"
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PARAMETER stop "<|endoftext|>"
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PARAMETER temperature 0.7
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PARAMETER top_p 0.9
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PARAMETER num_ctx 4096
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SYSTEM """Du bist ein freundlicher Deutschlehrer für A1-B1 Lernende. Erkläre Grammatikfehler klar und einfach. Beurteile grammatische Korrektheit sorgfältig."""
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```
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3. Create and run:
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```bash
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ollama create qwen3-german-teacher -f Modelfile
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ollama run qwen3-german-teacher "Is 'Ich habe nach Berlin gefahren' correct?"
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```
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## Example Interactions
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### Grammar Error Detection
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**User**: Is this German sentence grammatically correct? "Ich habe nach Berlin gefahren."
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**Model**: No, this sentence is incorrect. The verb "fahren" describes movement from one place to another, so it requires "sein" as the auxiliary verb, not "haben".
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**Correct**: "Ich **bin** nach Berlin gefahren."
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### Grammar Explanation
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**User**: Explain when to use "sein" vs "haben" in the Perfekt tense.
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**Model**: In German, most verbs use "haben" in the Perfekt tense, but verbs that describe:
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1. **Movement from A to B**: gehen, fahren, fliegen, kommen, laufen
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2. **Change of state**: aufwachen, einschlafen, sterben, werden
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These verbs use "sein" instead. For example:
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- Ich **bin** nach Hause gegangen. (movement)
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- Er **ist** eingeschlafen. (change of state)
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### Conjugation Help
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**User**: Conjugate "sein" in present tense.
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**Model**: Here is the conjugation of "sein" (to be) in present tense:
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| Person | Conjugation |
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|--------|-------------|
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| ich | bin |
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| du | bist |
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| er/sie/es | ist |
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| wir | sind |
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| ihr | seid |
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| sie/Sie | sind |
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## Limitations
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- Optimized for A1-B1 level German; may oversimplify advanced grammar concepts
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- Focused on grammar teaching; not designed for creative writing or translation
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- Best performance with clear, focused grammar questions
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## Training Methodology
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### Research-Informed Approach
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This model was developed using insights from recent research on instruction-tuning and continual learning:
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#### GRAPE Data Selection
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Based on the [GRAPE paper (Feb 2025)](https://arxiv.org/abs/2502.04194):
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> "Instructions paired with responses sampled from other LLMs are often **out of the distribution of the target model**, which can lead to diminishing returns and even hurt performance"
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**Key insight**: Rather than using responses generated by larger models (GPT-4, Claude), we curated training examples that align with Qwen3's natural output distribution. This prevents the model from learning patterns it cannot reliably reproduce.
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#### CoLA-Style Judgment Training
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The breakthrough in V4 was adding 25% **explicit grammaticality judgment examples**. This teaches the model to reason about correctness rather than just generate correct text:
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```
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User: Ist der Satz grammatisch korrekt? "Der Frau ist schön."
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Assistant: Nein, der Satz ist nicht korrekt.
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Fehler: "Der" ist maskulin, aber "Frau" ist feminin.
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Korrektur: "Die Frau ist schön."
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```
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#### Lessons from EWC/Fisher Information Research
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From [arXiv:2502.11756](https://arxiv.org/html/2502.11756v1) on Fisher Information computation:
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- **EXACT computation outperforms approximations**
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- Minimum 500 samples for reliable Fisher estimation
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- Device consistency (GPU-only) is critical
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These insights from our earlier SmolLM3 experiments (V5/V6 with Elastic Weight Consolidation) informed our dataset composition decisions for Qwen3-V4.
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## Training Details
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### Multi-Stage Finetuning: Lessons Learned
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This project was inspired by the 3-stage finetuning approach described in [MiroThinker (arXiv:2511.11793)](https://arxiv.org/abs/2511.11793):
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1. **Stage 1: SFT** (Supervised Fine-Tuning)
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2. **Stage 2: DPO** (Direct Preference Optimization)
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3. **Stage 3: RL/GRPO** (Reinforcement Learning with Grammar Rewards)
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Our training script design followed the MiroThinker paper's architecture, including:
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- **Higher LoRA rank (r=32, alpha=64)** as recommended for multi-stage training stability
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- **Full target modules** (q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj) for comprehensive adaptation
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However, **this model uses only SFT** because our experiments with preference optimization showed a fundamental trade-off:
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#### Why DPO/SimPO Failed for Our Use Case
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| Model | CoLA MCC | GEC F1 | Generation | Overall | Status |
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|-------|----------|--------|------------|---------|--------|
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| **V6 SFT (Baseline)** | **0.624** | **0.191** | 3.29 | **0.516** | Reference |
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| V8 (DPO) | 0.583 | 0.063 | 3.63 | 0.473 | -8% overall |
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| V9 (SimPO) | 0.567 | 0.073 | **3.72** | 0.479 | -7% overall |
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**Key findings**:
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- DPO improved generation quality (+10%) but **destroyed GEC accuracy (-67%)**
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- SimPO achieved best generation (3.72) but still regressed accuracy significantly
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- This confirms the "alignment tax" documented in 2025 research: 76% of preference optimization causes regression on specific tasks
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For grammar teaching, **accuracy is more important than fluency**, so we stayed with pure SFT. The V4 dataset composition (25% CoLA-style judgment examples) proved more effective than preference optimization for our metrics.
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### SFT Training Configuration
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Configuration based on [MiroThinker](https://arxiv.org/abs/2511.11793) recommendations for multi-stage training:
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```
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Base Model: Qwen/Qwen3-4B
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LoRA Configuration:
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- Rank (r): 32
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- Alpha: 64
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- Target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
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- Dropout: 0
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Training Configuration:
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- Epochs: 2
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- Learning Rate: 2e-4 (linear decay)
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- Batch Size: 2 (effective: 8 with gradient accumulation)
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- Warmup: 10%
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- Precision: BF16
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- Optimizer: AdamW 8-bit
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```
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The SFT stage trains on ~9,000 curated examples covering grammar judgment, error correction, and teaching explanations.
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### Deployment Pipeline
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After SFT training, the model goes through:
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#### 1. PEFT Merge
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LoRA adapters are merged into the base model:
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```python
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from peft import PeftModel
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from transformers import AutoModelForCausalLM
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base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B")
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model = PeftModel.from_pretrained(base_model, "lora_adapters/")
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model = model.merge_and_unload()
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model.save_pretrained("merged_model/", safe_serialization=True)
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```
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#### 2. GGUF Quantization
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For efficient local inference:
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```bash
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||||||
|
python convert_hf_to_gguf.py merged_model/ --outtype bf16 --outfile model-bf16.gguf
|
||||||
|
llama-quantize model-bf16.gguf model-Q4_K_M.gguf Q4_K_M
|
||||||
|
```
|
||||||
|
|
||||||
|
The Q4_K_M quantization reduces model size from ~8GB to 2.5GB while maintaining high quality.
|
||||||
|
|
||||||
|
### Technical Specifications
|
||||||
|
|
||||||
|
- **Framework**: Unsloth + Transformers + TRL + PEFT
|
||||||
|
- **Hardware**: NVIDIA RTX 4090 (24GB VRAM)
|
||||||
|
- **Training Time**: ~45 minutes for 2 epochs
|
||||||
|
- **Quantization**: GGUF Q4_K_M (2.5GB)
|
||||||
|
|
||||||
|
## Citation
|
||||||
|
|
||||||
|
If you use this model, please cite:
|
||||||
|
|
||||||
|
```bibtex
|
||||||
|
@misc{qwen3-4b-german-teacher-2025,
|
||||||
|
author = {Jaigouk Kim},
|
||||||
|
title = {Qwen3-4B German Teacher: A Finetuned Model for German Grammar Teaching},
|
||||||
|
year = {2025},
|
||||||
|
publisher = {HuggingFace},
|
||||||
|
url = {https://huggingface.co/jaigouk/qwen3-4b-german-teacher}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## License
|
||||||
|
|
||||||
|
This model is released under the Apache 2.0 license, following the base Qwen3 model license.
|
||||||
|
|
||||||
|
## Acknowledgments
|
||||||
|
|
||||||
|
- [Qwen Team](https://github.com/QwenLM/Qwen3) for the excellent base model
|
||||||
|
- [Unsloth](https://github.com/unslothai/unsloth) for efficient finetuning tools
|
||||||
28
added_tokens.json
Normal file
28
added_tokens.json
Normal file
@@ -0,0 +1,28 @@
|
|||||||
|
{
|
||||||
|
"</think>": 151668,
|
||||||
|
"</tool_call>": 151658,
|
||||||
|
"</tool_response>": 151666,
|
||||||
|
"<think>": 151667,
|
||||||
|
"<tool_call>": 151657,
|
||||||
|
"<tool_response>": 151665,
|
||||||
|
"<|box_end|>": 151649,
|
||||||
|
"<|box_start|>": 151648,
|
||||||
|
"<|endoftext|>": 151643,
|
||||||
|
"<|file_sep|>": 151664,
|
||||||
|
"<|fim_middle|>": 151660,
|
||||||
|
"<|fim_pad|>": 151662,
|
||||||
|
"<|fim_prefix|>": 151659,
|
||||||
|
"<|fim_suffix|>": 151661,
|
||||||
|
"<|im_end|>": 151645,
|
||||||
|
"<|im_start|>": 151644,
|
||||||
|
"<|image_pad|>": 151655,
|
||||||
|
"<|object_ref_end|>": 151647,
|
||||||
|
"<|object_ref_start|>": 151646,
|
||||||
|
"<|quad_end|>": 151651,
|
||||||
|
"<|quad_start|>": 151650,
|
||||||
|
"<|repo_name|>": 151663,
|
||||||
|
"<|video_pad|>": 151656,
|
||||||
|
"<|vision_end|>": 151653,
|
||||||
|
"<|vision_pad|>": 151654,
|
||||||
|
"<|vision_start|>": 151652
|
||||||
|
}
|
||||||
97
chat_template.jinja
Normal file
97
chat_template.jinja
Normal file
@@ -0,0 +1,97 @@
|
|||||||
|
{%- 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 forward_message in messages %}
|
||||||
|
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||||
|
{%- set message = messages[index] %}
|
||||||
|
{%- set tool_start = '<tool_response>' %}
|
||||||
|
{%- set tool_start_length = tool_start|length %}
|
||||||
|
{%- set start_of_message = message.content[:tool_start_length] %}
|
||||||
|
{%- set tool_end = '</tool_response>' %}
|
||||||
|
{%- set tool_end_length = tool_end|length %}
|
||||||
|
{%- set start_pos = (message.content|length) - tool_end_length %}
|
||||||
|
{%- if start_pos < 0 %}
|
||||||
|
{%- set start_pos = 0 %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- set end_of_message = message.content[start_pos:] %}
|
||||||
|
{%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %}
|
||||||
|
{%- set ns.multi_step_tool = false %}
|
||||||
|
{%- set ns.last_query_index = index %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- for message in messages %}
|
||||||
|
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||||
|
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
||||||
|
{%- elif message.role == "assistant" %}
|
||||||
|
{%- set content = message.content %}
|
||||||
|
{%- set reasoning_content = '' %}
|
||||||
|
{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
|
||||||
|
{%- set reasoning_content = message.reasoning_content %}
|
||||||
|
{%- else %}
|
||||||
|
{%- if '</think>' in message.content %}
|
||||||
|
{%- set content = (message.content.split('</think>')|last).lstrip('\n') %}
|
||||||
|
{%- set reasoning_content = (message.content.split('</think>')|first).rstrip('\n') %}
|
||||||
|
{%- set reasoning_content = (reasoning_content.split('<think>')|last).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' }}
|
||||||
|
{{- message.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,
|
||||||
|
"bos_token_id": 151643,
|
||||||
|
"dtype": "bfloat16",
|
||||||
|
"eos_token_id": 151645,
|
||||||
|
"head_dim": 128,
|
||||||
|
"hidden_act": "silu",
|
||||||
|
"hidden_size": 2560,
|
||||||
|
"initializer_range": 0.02,
|
||||||
|
"intermediate_size": 9728,
|
||||||
|
"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,
|
||||||
|
"rms_norm_eps": 1e-06,
|
||||||
|
"rope_scaling": null,
|
||||||
|
"rope_theta": 1000000,
|
||||||
|
"sliding_window": null,
|
||||||
|
"tie_word_embeddings": true,
|
||||||
|
"transformers_version": "4.57.0",
|
||||||
|
"use_cache": true,
|
||||||
|
"use_sliding_window": false,
|
||||||
|
"vocab_size": 151936
|
||||||
|
}
|
||||||
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": "4.57.0"
|
||||||
|
}
|
||||||
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
3
model-00001-of-00002.safetensors
Normal file
3
model-00001-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:e1b1c688b7760086eb4b62976c82cae4b5c905ea421fc1b611cf73d82a783119
|
||||||
|
size 4967215360
|
||||||
3
model-00002-of-00002.safetensors
Normal file
3
model-00002-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:55a4a7e9ebc0d28f230043fbb14b19110162c5c8a0651a4d312d81c7afac29c7
|
||||||
|
size 3077766632
|
||||||
406
model.safetensors.index.json
Normal file
406
model.safetensors.index.json
Normal file
@@ -0,0 +1,406 @@
|
|||||||
|
{
|
||||||
|
"metadata": {
|
||||||
|
"total_parameters": 4022468096,
|
||||||
|
"total_size": 8044936192
|
||||||
|
},
|
||||||
|
"weight_map": {
|
||||||
|
"model.embed_tokens.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
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3
qwen3-german-teacher-Q4_K_M.gguf
Normal file
3
qwen3-german-teacher-Q4_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:215e615126933c705c0f9b96705243956883d8594861d2ed4507ae0f9c1f5e22
|
||||||
|
size 2497280832
|
||||||
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": "<|vision_pad|>",
|
||||||
|
"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,
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|im_end|>",
|
||||||
|
"errors": "replace",
|
||||||
|
"extra_special_tokens": {},
|
||||||
|
"model_max_length": 40960,
|
||||||
|
"pad_token": "<|vision_pad|>",
|
||||||
|
"padding_side": "left",
|
||||||
|
"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