Update README.md

README.md

@@ -17,36 +17,19 @@ tags:
 
 # Qwen3-4B-DBbase_AW_345NoEAd_ALFformat_QH5L4R5_1392-r16a32-B16-2ep-5e6
 
-This repository provides a **LoRA adapter** fine-tuned from
-**Qwen/Qwen3-4B-Instruct-2507** using **LoRA + Unsloth**.
+This repository contains the **full-merged 16-bit weights** fine-tuned from
+**Qwen/Qwen3-4B-Instruct-2507** using **LoRA + Unsloth**. 
+No adapter loading is required.
 
 
-## Training Objective
-
-This model is trained to improve **multi-turn agent task performance**
-on ALFWorld (household tasks) and DBBench (database operations).
-
-Loss is applied to **all assistant turns** in the multi-turn trajectory,
-enabling the model to learn environment observation, action selection,
-tool use, and recovery from errors.
-
-## Training Configuration
-
-- Base model: Qwen/Qwen3-4B-Instruct-2507
-- Method: LoRA (full precision base)
-- Max sequence length: 8192
-- Epochs: 2
-- Learning rate: 5e-06
-- LoRA: r=16, alpha=32, use_rslora=False
-- TOTAL_BATCH_SIZE: 16
 
 ## Usage
-
+Since this is a merged model, you can use it directly with `transformers`.
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
-model_id = "hara-CU/Qwen3-4B-DBbase_AW_345NoEAd_ALFformat_QH5L4R5_1392-r16a32-B16-2ep-5e6"
+model_id = "hara-CU/Advanced_FinalCandidate_482"
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(