Model: fn-aka-mur/qw3-4b-v17-gs180 Source: Original Platform
base_model, datasets, language, license, library_name, pipeline_tag, tags
| base_model | datasets | language | license | library_name | pipeline_tag | tags | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Qwen/Qwen3-4B-Instruct-2507 |
|
|
apache-2.0 | HuggingFace Transformers | text-generation |
|
Qwen3-4B-Instruct-2507-LoRA-AgentBench
This repository provides a RL'ed model fine-tuned from Qwen/Qwen3-4B-Instruct-2507 using HuggingFace Transformers.
Training Objective
This model is trained to improve multi-turn agent task performance on ALFWorld (household tasks) and DBBench (database operations).
Training Configuration
- Base model: Qwen/Qwen3-4B-Instruct-2507
- Method: Agentic Reinforcement Learning
- Max sequence length: 8192
- Learning rate: 1e-06
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch
base = "fujiki/qw3-4b-v17-gs180"
tokenizer = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(
base,
torch_dtype=torch.float16,
device_map="auto",
)
Sources & Terms (IMPORTANT)
Training data: u-10bei/sft_alfworld_trajectory_dataset_v5, u-10bei/dbbench_sft_dataset_react_v4 and task enviromnents for the Agentic RL of LLM.
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.
Description
Languages
Jinja
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