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Qwen 3.5 Reasoning (Claude 4.6 Distilled)
Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled
A 27B powerhouse distilled from Claude 4.6 Opus. Built for deep analytical reasoning and stable agentic performance in the watch market.
How to Use
To get started, install the `transformers` library:
pip install transformersThen, use the following snippet to load the model:
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
# Your inference code here...Available Versions
| Tag / Variant | Size | Format | Download |
|---|---|---|---|
| Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled:unslothqwenqwen3.5reasoningchain-of-thoughtDense | 16.5GB | BF16 | Link |
Model Details
Teacher Model
Claude-4.6-Opus
Distillation Method
Knowledge Distillation (Logits)
Training Dataset
Flickr30k (Conceptual)
Primary Task
Multimodal Generation
Performance Metrics (Example)
| Metric | Student Model | Teacher Model |
|---|---|---|
| Model Size | 16.5GB | 8.5GB |
| BLEU Score | 28.5 | 30.1 |