Update README.md

README.md

@@ -14,14 +14,14 @@ tags:
 ---
 # **Primal-Mini-3B-Exp**  
 
-Primal-Mini-3B-Exp is based on the Qwen 2.5 14B modality architecture, designed to enhance the reasoning capabilities of 3B-parameter models. It has been fine-tuned on a Synthetic dataset entries based on one half of Qwen’s QWQ and DeepSeek R1, further optimizing its chain-of-thought (CoT) reasoning and logical problem-solving abilities. The model demonstrates significant improvements in context understanding, structured data processing, and long-context comprehension, making it ideal for complex reasoning tasks, instruction-following, and text generation.  
+Primal-Mini-3B-Exp is based on the Qwen 3B modality architecture, designed to enhance the reasoning capabilities of 3B-parameter models. It has been fine-tuned on a synthetic dataset derived from a subset of Qwen’s QWQ and DeepSeek R1, further optimizing its chain-of-thought (CoT) reasoning and logical problem-solving abilities. The model demonstrates significant improvements in context understanding, structured data processing, and long-context comprehension, making it ideal for complex reasoning tasks, instruction-following, and text generation.  
 
 ### **Key Improvements**  
 1. **Advanced Reasoning & Logic**: Optimized for multi-step problem-solving, logical deduction, and contextual analysis.  
-2. **Fine-Tuned Instruction Following**: Generates precise responses, structured outputs (e.g., JSON), and extended long-form text (8K+ tokens).  
+2. **Fine-Tuned Instruction Following**: Generates precise responses, structured outputs (e.g., JSON), and extended long-form text (4K+ tokens).  
 3. **Greater Adaptability**: Excels in role-playing, multi-turn dialogues, and diverse system prompts.  
-4. **Long-Context Support**: Handles up to **128K tokens** and generates up to **8K tokens** per output.  
-5. **Multilingual Proficiency**: Supports over **29 languages**, including Chinese, English, French, Spanish, Portuguese, German, and more.  
+4. **Long-Context Support**: Handles up to **64K tokens** and generates up to **4K tokens** per output.  
+5. **Multilingual Proficiency**: Supports over **20 languages**, including Chinese, English, French, Spanish, Portuguese, German, and more.  
 
 ### **Quickstart with Transformers**  
 
@@ -52,7 +52,7 @@ model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
 
 generated_ids = model.generate(
     **model_inputs,
-    max_new_tokens=512
+    max_new_tokens=256
 )
 generated_ids = [
     output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
@@ -67,12 +67,12 @@ print(response)
 - **Mathematical & Scientific Computation**: Supports theorem proving, complex calculations, and scientific knowledge retrieval.  
 - **Code Generation & Debugging**: Generates optimized code, detects errors, and improves programming workflows.  
 - **Structured Data Analysis**: Processes tables, JSON, and structured formats for data-centric applications.  
-- **Multilingual Reasoning & Translation**: High proficiency across **29+ languages** for international applications.  
+- **Multilingual Reasoning & Translation**: High proficiency across **20+ languages** for international applications.  
 - **Extended Text Generation**: Capable of generating research papers, instructional guides, and in-depth reports.  
 
 ### **Limitations**  
-1. **High Computational Requirements**: Due to its **3B parameters** and **128K context support**, it requires powerful GPUs or TPUs for efficient inference.  
+1. **Moderate Computational Requirements**: Requires **mid-end consumer GPUs** for optimal inference.  
 2. **Language-Specific Variability**: Performance may differ across supported languages, especially for low-resource languages.  
 3. **Potential Error Accumulation**: Long-form text generation can introduce inconsistencies over extended outputs.  
 4. **Limited Real-World Awareness**: Knowledge is restricted to training data and may not reflect recent world events.  
-5. **Prompt Sensitivity**: The quality of responses depends on the specificity and clarity of the input prompt.
+5. **Prompt Sensitivity**: The quality of responses depends on the specificity and clarity of the input prompt.