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Model: moushi21/agent-bench-merged12
Source: Original Platform

README.md

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+---
+base_model: Qwen/Qwen3-4B-Instruct-2507
+datasets:
+- u-10bei/sft_alfworld_trajectory_dataset
+- u-10bei/sft_alfworld_trajectory_dataset_v2
+- u-10bei/sft_alfworld_trajectory_dataset_v3
+- u-10bei/sft_alfworld_trajectory_dataset_v4
+- u-10bei/sft_alfworld_trajectory_dataset_v5
+- u-10bei/dbbench_sft_dataset_react
+- u-10bei/dbbench_sft_dataset_react_v2
+- u-10bei/dbbench_sft_dataset_react_v3
+- u-10bei/dbbench_sft_dataset_react_v4
+language:
+- en
+license: apache-2.0
+library_name: mergekit
+pipeline_tag: text-generation
+tags:
+- merge
+- ties
+- agent
+- tool-use
+- alfworld
+- dbbench
+---
+
+## Performance
+The model shows balanced performance across agentic tasks:
+- **ALFWorld**: 0.60 (Pass@1)
+- **DBBench**: 0.5353
+
+# Qwen3-4B Agent TIES Merge v1.2
+This repository provides a merged model optimized for agentic tasks, created by merging specialized LoRA adapters into the base model **Qwen/Qwen3-4B-Instruct-2507**.
+
+The merge was performed using the **TIES-Merging** method via **Mergekit**, combining expertise in ALFWorld trajectories and DBBench (SQL) tasks.
+
+This repository contains **full model weights**, ready for inference without needing to load separate adapters.
+
+## Merge Details
+This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) method.
+
+### Merge Method
+- **Method**: `ties`
+- **Base Model**: `Qwen/Qwen3-4B-Instruct-2507`
+- **Dtype**: `bfloat16`
+
+### Configuration
+The following mergekit-yaml configuration was used to produce this model:
+
+```config.yaml
+merge_method: ties
+base_model: Qwen/Qwen3-4B-Instruct-2507
+dtype: bfloat16
+models:
+  - model: moushi21/agent-bench-alfworld-merged3
+    parameters:
+      weight: 1.0    # ALF Main
+      density: 0.3   # 70% Noise Cut
+  - model: moushi21/agent-bench-dbbench-merged4
+    parameters:
+      weight: 0.3    # DB
+      density: 0.3   # 70% Noise Cut
+```
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "moushi21/agent-bench-merged12"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+```
+
+## Sources & Terms (IMPORTANT)
+
+### Training Data (Source Model Lineage)
+The source models utilized the following datasets for fine-tuning:
+* **ALFWorld**: `u-10bei/sft_alfworld_trajectory_dataset` (v1 to v5)
+* **DBBench**: `u-10bei/dbbench_sft_dataset_react` (v1 to v4)
+
+### License & Compliance
+* **Dataset License**: MIT License. These datasets are 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 (**Qwen3-4B-Instruct-2507**).
+