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README.md

@@ -1,3 +1,21 @@
+---
+language: en
+license: apache-2.0
+tags:
+- social-media
+- content-analysis
+- deepseek
+- llama
+- unsloth
+datasets:
+- custom
+metrics:
+- accuracy
+library_name: transformers
+pipeline_tag: text-generation
+widget:
+- text: "Let me show you how to track your expenses with this simple spreadsheet template. First, create columns for date, category, and amount. Then, use the SUM function to automatically calculate your total spending..."
+---
 
 # Social Media Content Analyzer
 
@@ -20,7 +38,7 @@ model = AutoModelForCausalLM.from_pretrained(model_id)
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 
 def generate_content_analysis(transcript, confidence_score):
-    prompt = f"""Below is a transcript from a social media video along with its confidence score. 
+    prompt = f"""Below is a transcript from a social media video along with its confidence score.
 Your task is to analyze the content and provide a detailed content critique analyzing the hook, reliability factor, relatability, and shareability.
 
 ### Transcript:
@@ -30,7 +48,7 @@ Your task is to analyze the content and provide a detailed content critique anal
 {confidence_score}
 
 ### Content Critique:"""
-    
+
     inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
     outputs = model.generate(
         input_ids=inputs.input_ids,