Update README.md

README.md

@@ -1,46 +1,46 @@
----
-    license: apache-2.0
-    tags:
-    - LoRA
-- 4-bit
-- BF16
-- FlashAttn2
-- Pokémon
-- EMA
-- fast-training
-- text-generation
-- chat
-- transformers
-    language: en
-    datasets:
-    - ogmatrixllm/pokemon-lore-instructions
-    finetuned_from: Qwen/Qwen2.5-7B-Instruct
-    tasks:
-    - text-generation
-    ---
-
-    # 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**.
-
-    ## 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
-
-    ## Usage
-
-    ```python
-    from transformers import AutoTokenizer, AutoModelForCausalLM
-
-    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))
+---
+license: apache-2.0
+tags:
+- LoRA
+- 4-bit
+- BF16
+- FlashAttn2
+- Pokémon
+- EMA
+- fast-training
+- text-generation
+- chat
+- transformers
+language: en
+datasets:
+- ogmatrixllm/pokemon-lore-instructions
+finetuned_from: Qwen/Qwen2.5-7B-Instruct
+tasks:
+- text-generation
+    ---
+
+    # 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**.
+
+    ## 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
+
+    ## Usage
+
+    ```python
+    from transformers import AutoTokenizer, AutoModelForCausalLM
+
+    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))