92 lines
2.7 KiB
Markdown
92 lines
2.7 KiB
Markdown
---
|
|
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**).
|
|
|