初始化项目，由ModelHub XC社区提供模型

Model: melon1891/agentbench-qwen3-4b-2stage-reasoning-20260228
Source: Original Platform

README.md

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+---
+base_model: melon1891/agentbench-qwen3-4b-lr5e6-20260224v2
+datasets:
+- melon1891/reasoning-chain-distilled-317
+language:
+- en
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- agent
+- tool-use
+- alfworld
+- dbbench
+---
+
+# agentbench-qwen3-4b-2stage-reasoning-20260228
+
+A full model fine-tuned from **melon1891/agentbench-qwen3-4b-lr5e6-20260224v2** using LoRA + Unsloth, with the adapter merged into the base model.
+
+## Training Objective
+
+This model is trained to improve **multi-turn agent task performance**
+on ALFWorld (household tasks) and DBBench (database operations).
+
+Loss is applied to **all assistant turns** in the multi-turn trajectory,
+enabling the model to learn environment observation, action selection,
+tool use, and recovery from errors.
+
+## Training Configuration
+
+- Base model: melon1891/agentbench-qwen3-4b-lr5e6-20260224v2
+- Method: LoRA (merged into base)
+- Max sequence length: 8192
+- Epochs: 3
+- Learning rate: 1e-06
+- LoRA: r=16, alpha=32
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("melon1891/agentbench-qwen3-4b-2stage-reasoning-20260228")
+tokenizer = AutoTokenizer.from_pretrained("melon1891/agentbench-qwen3-4b-2stage-reasoning-20260228")
+```
+
+## Sources & Terms (IMPORTANT)
+
+Training data: melon1891/reasoning-chain-distilled-317
+
+Dataset License: MIT License. This dataset is used and distributed under the terms of the MIT License.
+Compliance: Users must comply with the MIT license (including copyright notice) and the base model's original terms of use.