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agentbenchfinal – AI Model by takayosh | AlphaNeural AI

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takayosh/
agentbenchfinal

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text-generation

u-10bei/sft_alfworld_trajectory_dataset_v5

u-10bei/dbbench_sft_dataset_react_v4

Qwen/Qwen2.5-7B-Instruct

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qwen2.5-7b-alf-dbb-merged-final

This repository provides a merged full model based on Qwen/Qwen2.5-7B-Instruct.

Model Construction Pipeline

Train LoRA adapter on ALFWorld
Train LoRA adapter on DBBench
Merge adapters using ties (density=0.1)
Apply additional stabilization fine-tuning (LoRA)
Merge final adapter into base model

This repository contains full merged weights (no adapter required).

Final Training Configuration

Base model: Qwen/Qwen2.5-7B-Instruct
Merge method: ties
Merge density: 0.1
Final stage epochs: 1
Learning rate: 1e-05
Final LoRA: r=16, alpha=16
Max sequence length: 2024

Datasets

u-10bei/sft_alfworld_trajectory_dataset_v5
u-10bei/dbbench_sft_dataset_react_v4

Additional distilled datasets were optionally included.

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "takayosh/agentbenchfinal"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype="auto",
    device_map="auto"
)

Sources & Terms (IMPORTANT)

Training data:

u-10bei/sft_alfworld_trajectory_dataset_v5
u-10bei/dbbench_sft_dataset_react_v4

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.