Update README.md

README.md

@@ -25,27 +25,28 @@ base_model:
 pipeline_tag: text-generation
 ---
 
-    # Qwen2.5-Coder-7B LoRA 4-bit BF16 w/ FlashAttn2, short seq=512 for faster iteration
+# Qwen2.5-Coder-7B LoRA 4-bit BF16 w/ FlashAttn2, short seq=512 for faster iteration
 
-    This is a LoRA-fused model based on **Qwen/Qwen2.5-7B-Instruct**.
+This is a LoRA-fused model based on **Qwen/Qwen2.5-7B-Instruct**.
 
-    ## Model Description
+## Model Description
 
-    - **Model Name**: Qwen2.5-Coder-7B LoRA 4-bit BF16 w/ FlashAttn2, short seq=512 for faster iteration  
-    - **Language**: en  
-    - **License**: apache-2.0  
-    - **Dataset**: ogmatrixllm/pokemon-lore-instructions  
-    - **Tags**: LoRA, 4-bit, BF16, FlashAttn2, Pokémon, EMA, fast-training, text-generation, chat, transformers
+- **Model Name**: Qwen2.5-Coder-7B LoRA 4-bit BF16 w/ FlashAttn2, short seq=512 for faster iteration  
+- **Language**: en  
+- **License**: apache-2.0  
+- **Dataset**: ogmatrixllm/pokemon-lore-instructions  
+- **Tags**: LoRA, 4-bit, BF16, FlashAttn2, Pokémon, EMA, fast-training, text-generation, chat, transformers
 
-    ## Usage
+## Usage
 
-    ```python
-    from transformers import AutoTokenizer, AutoModelForCausalLM
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-    tokenizer = AutoTokenizer.from_pretrained("ogmatrixllm/arcadex-llm")
-    model = AutoModelForCausalLM.from_pretrained("ogmatrixllm/arcadex-llm")
+tokenizer = AutoTokenizer.from_pretrained("ogmatrixllm/arcadex-llm")
+model = AutoModelForCausalLM.from_pretrained("ogmatrixllm/arcadex-llm")
 
-    prompt = "Hello, world!"
-    inputs = tokenizer(prompt, return_tensors="pt")
-    outputs = model.generate(**inputs)
-    print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+prompt = "Hello, world!"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```