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README.md

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+---
+license: apache-2.0
+language:
+- bn
+- en
+base_model: Qwen/Qwen3.6-27B
+tags:
+- qwen3_5
+- fine-tuned
+model-index:
+- name: DropLychee-1.2
+  results:
+  - task:
+      type: text-generation
+      name: GPQA Diamond (zero-shot)
+    dataset:
+      name: GPQA Diamond
+      type: Idavidrein/gpqa
+    metrics:
+    - type: acc_norm
+      value: 42.0
+      name: accuracy (normalized)
+  - task:
+      type: text-generation
+      name: MMLU-Pro (5-shot)
+    dataset:
+      name: MMLU-Pro
+      type: TIGER-Lab/MMLU-Pro
+    metrics:
+    - type: exact_match
+      value: 64.0
+      name: exact match
+---
+
+# DropLychee 1.2
+
+Fine-tuned model based on Qwen3.6-27B (LoRA fine-tune, 500 steps).
+
+## Evaluation
+
+Evaluated using [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) on 2026-07-12.
+
+| Benchmark | Score |
+|---|---|
+| GPQA Diamond (0-shot) | 42.0% (acc_norm) |
+| MMLU-Pro (5-shot) | 64.0% (exact_match) |
+
+Total evaluation time: ~2.3 hours on RTX PRO 6000 Blackwell (96GB).
+
+## Usage
+
+\`\`\`python
+from unsloth import FastLanguageModel
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name="droplychee/DropLychee-1.2",
+    max_seq_length=2048,
+    dtype=None,
+    load_in_4bit=False,
+)
+FastLanguageModel.for_inference(model)
+\`\`\`