Update README.md

README.md

@@ -1,5 +1,4 @@
-Below is an improved version of the README in Markdown format. You can copy and paste the following text into your README file.
-
+Model
 ---
 
 # MasterControlAIML R1-Qwen2.5-1.5b SFT R1 JSON Unstructured-To-Structured LoRA Model
@@ -76,7 +75,7 @@ from unsloth import FastLanguageModel
 import torch
 
 # Specify the model name
-MODEL = "MasterControlAIML/R1-Qwen2.5-1.5b-SFT-R1-JSON-Unstructured-To-Structured-lora"
+MODEL = "MasterControlAIML/DeepSeek-R1-Qwen2.5-1.5b-SFT-R1-JSON-Unstructured-To-Structured"
 
 # Load the model and tokenizer
 model, tokenizer = FastLanguageModel.from_pretrained(
@@ -118,7 +117,7 @@ If you prefer to use Hugging Face's Transformers directly, here’s an alternati
 from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
 import torch
 
-MODEL = "MasterControlAIML/R1-Qwen2.5-1.5b-SFT-R1-JSON-Unstructured-To-Structured-lora"
+MODEL = "MasterControlAIML/DeepSeek-R1-Qwen2.5-1.5b-SFT-R1-JSON-Unstructured-To-Structured"
 
 # Initialize tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained(MODEL)
@@ -133,7 +132,7 @@ Below is an instruction that describes a task, paired with an input that provide
 """
 
 # Define your text input
-TEXT = "Provide a detailed explanation of the QA processes in manufacturing."
+TEXT = ""
 prompt = ALPACA_PROMPT.format(TEXT, "")
 inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
 text_streamer = TextStreamer(tokenizer)