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Llama3.2-1B-Grpo-Exp

The Llama3.2-1B-Grpo-Exp is a fine-tuned version of the Llama-3.1-8B base model, further enhanced with the GSM8K dataset for superior text generation and mathematical reasoning. This model is designed for advanced reasoning, structured problem-solving, and contextually rich outputs, making it an excellent choice for applications in education, programming, research, and creative writing.

With its optimized architecture, Llama3.2-1B-Grpo-Exp excels at:

  • Logical reasoning and step-by-step problem-solving
  • Mathematical and coding tasks, leveraging specialized expert models
  • Generating long-form content (up to 8K tokens) with improved coherence
  • Understanding structured data, including tables and JSON outputs
  • Following instructions and adapting to diverse system prompts, making it ideal for chatbots and AI assistants

Key Features

  • Supports long-context processing of up to 128K tokens
  • Fine-tuned using Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF)

Model Architecture

Llama3.2-1B-Grpo-Exp is built on the optimized transformer architecture of Llama-3.1-8B, integrating enhanced dataset logits from GSM8K for better mathematical reasoning and structured output generation.

Using with transformers

To run conversational inference using transformers >= 4.43.0, use the pipeline abstraction or leverage the generate() function with the Auto classes.

Ensure your environment is updated with:

pip install --upgrade transformers  

Example Usage

import torch  
from transformers import pipeline  

model_id = "prithivMLmods/Llama3.2-1B-Grpo-Exp"  
pipe = pipeline(  
    "text-generation",  
    model=model_id,  
    torch_dtype=torch.bfloat16,  
    device_map="auto",  
)  

messages = [  
    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},  
    {"role": "user", "content": "Who are you?"},  
]  

outputs = pipe(  
    messages,  
    max_new_tokens=256,  
)  
print(outputs[0]["generated_text"][-1])  

Intended Use

Llama3.2-1B-Grpo-Exp is designed for a wide range of applications requiring deep reasoning, structured outputs, and logical text generation. It is particularly suited for:

  • Education & Research: Generating detailed explanations, step-by-step solutions, and structured academic content.
  • Programming & Code Generation: Assisting in code writing, debugging, and algorithm explanations with improved logic structuring.
  • AI Chatbots & Assistants: Providing context-aware, instruction-following responses for conversational AI applications.
  • Creative Writing: Generating high-quality stories, articles, and structured narratives with coherence.
  • Data Analysis & Structured Output Generation: Interpreting and generating JSON, tables, and formatted outputs for structured data processing.

Limitations

While Llama3.2-1B-Grpo-Exp is optimized for deep reasoning and structured outputs, it has some limitations:

  1. Not a Real-time Knowledge Source

    • The model is trained on a fixed dataset and does not have real-time internet access. It may not provide up-to-date information on rapidly evolving topics.
  2. Potential Biases

    • As with all AI models, responses may reflect biases present in the training data. Users should critically evaluate outputs, especially in sensitive domains.
  3. Mathematical & Logical Reasoning Constraints

    • While strong in step-by-step reasoning, it may occasionally produce incorrect mathematical calculations or logical inconsistencies. External verification is recommended for critical applications.
  4. Handling of Extremely Long Contexts

    • While it supports up to 128K tokens, efficiency and coherence may degrade when processing very long documents or conversations.
  5. Limited Handling of Ambiguity

    • The model may struggle with highly ambiguous or context-dependent queries, sometimes generating plausible but incorrect responses.
  6. Ethical & Compliance Considerations

    • Not intended for generating misinformation, automating legal or medical decisions, or other high-risk applications without human oversight.
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