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README.md
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base_model: TeichAI/Qwen3-4B-Thinking-2507-Claude-4.5-Opus-High-Reasoning-Distill
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- qwen3
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license: apache-2.0
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datasets:
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- TeichAI/claude-4.5-opus-250x
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---
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# Qwen3 4B Thinking 2507 x Claude 4.5 Opus (High Reasoning) Distill
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This model was trained on a **Claude Opus 4.5 (reasoning)** dataset with a high reasoning effort.
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- 🤖 Related Models:
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| Model | Effective parameters | Active parameters |
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| ------------- | ------------- | ------------- |
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| [`TeichAI/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-GGUF`](https://huggingface.co/TeichAI/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-GGUF) | 8 B | 8 B |
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- 🧬 Datasets:
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- `TeichAI/claude-4.5-opus-high-reasoning-250x`
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- 🏗 Base Model:
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- `unsloth/Qwen3-4B-Thinking-2507`
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- ⚡ Use cases:
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- Coding
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- Science
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- General Purpose
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- ∑ Stats (Dataset)
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- Costs: $ 52.3 (USD)
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- Total tokens (input + output): 2.13 M
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+
---
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base_model: TeichAI/Qwen3-4B-Thinking-2507-Claude-4.5-Opus-High-Reasoning-Distill
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| 3 |
+
tags:
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+
- text-generation-inference
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| 5 |
+
- transformers
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| 6 |
+
- unsloth
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| 7 |
+
- qwen3
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| 8 |
+
license: apache-2.0
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| 9 |
+
datasets:
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| 10 |
+
- TeichAI/claude-4.5-opus-high-reasoning-250x
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| 11 |
+
---
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+
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+
# Qwen3 4B Thinking 2507 x Claude 4.5 Opus (High Reasoning) Distill
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| 14 |
+
|
| 15 |
+
This model was trained on a **Claude Opus 4.5 (reasoning)** dataset with a high reasoning effort.
|
| 16 |
+
|
| 17 |
+
- 🤖 Related Models:
|
| 18 |
+
| Model | Effective parameters | Active parameters |
|
| 19 |
+
| ------------- | ------------- | ------------- |
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| 20 |
+
| [`TeichAI/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-GGUF`](https://huggingface.co/TeichAI/Qwen3-8B-Claude-4.5-Opus-High-Reasoning-Distill-GGUF) | 8 B | 8 B |
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| 21 |
+
|
| 22 |
+
- 🧬 Datasets:
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| 23 |
+
- `TeichAI/claude-4.5-opus-high-reasoning-250x`
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| 24 |
+
|
| 25 |
+
- 🏗 Base Model:
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| 26 |
+
- `unsloth/Qwen3-4B-Thinking-2507`
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| 27 |
+
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| 28 |
+
- ⚡ Use cases:
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| 29 |
+
- Coding
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| 30 |
+
- Science
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| 31 |
+
- General Purpose
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| 32 |
+
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| 33 |
+
- ∑ Stats (Dataset)
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| 34 |
+
- Costs: $ 52.3 (USD)
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| 35 |
+
- Total tokens (input + output): 2.13 M
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