Beta

Explore
Marketplace
Neural Labs
Chat
Wallet
Docs

Beta

Explore Marketplace Neural Labs Wallet Docs

Build

Manage

My assets Manage wallet Organization

Community

Discord X (Twitter)Telegram

Docs Privacy Policy Terms and Conditions

Proud member of

Proud member of

Docs Cookie Policy

Privacy Policy Terms and Conditions

© 2026 AlphaNeural AI. All rights reserved.

qwe2.5-7b-AWQ-nako13-agentbench-lora – AI Model by nakotsuko13 | AlphaNeural AI

You can deploy this model and start earning money today!

nakotsuko13/
qwe2.5-7b-AWQ-nako13-agentbench-lora

like

0

text-generation

nakotsuko13/distilled_dataset_mixed_v3

Qwen/Qwen2.5-7B-Instruct

Views

No views yet

Agent SFT Model (ALFWorld & DBBench)

This repository provides a LoRA adapter fine-tuned from Qwen/Qwen2.5-7B-Instruct using LoRA + Unsloth.

Training Objective

This adapter is trained to improve multi-turn agent task performance on:

ALFWorld: Household interaction tasks.
DBBench: Complex SQL database operations.

Training Configuration

Base model: Qwen/Qwen2.5-7B-Instruct
Max sequence length: 2048
Epochs: 1
Learning rate: 1e-07
LoRA: r=64, alpha=128

Training Data

nakotsuko13/distilled_dataset_mixed_v3

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

base = "Qwen/Qwen2.5-7B-Instruct"
model = AutoModelForCausalLM.from_pretrained(base, torch_dtype=torch.float16, device_map="auto")
model = PeftModel.from_pretrained(model, "your_id/your-repo")