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README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model:
+- meta-llama/Llama-3.2-3B-Instruct
+library_name: transformers
+---
+# Thought-Ranked Llama 3.2 3B v2
+
+## What's New in v2?
+
+The biggest improvement in v2 is how the model thinks through problems. Instead of just one level of thoughts, it can now explore up to 6 levels deep, building on its best ideas at each step. Think of it like having a conversation with yourself, where each new thought builds on your previous best insight.
+
+## How It Works
+
+Let's look at an example. When asked "What would happen if the moon disappeared?", the model might think:
+
+```
+<thoughts>
+<thought>First, I should consider the moon's main effects on Earth</thought>
+<thought>The moon controls our tides, so ocean patterns would change dramatically</thought>
+<thought>Without the moon's gravitational pull, Earth's rotation would become unstable</thought>
+<thought>This would lead to extreme climate changes and disrupted ecosystems</thought>
+<thought>The loss of moonlight would affect nocturnal animals and human culture</thought>
+<thought>Combining all these effects, we'd see a cascade of environmental changes</thought>
+</thoughts>
+
+The disappearance of the moon would have far-reaching consequences for Earth...
+[detailed answer follows]
+```
+
+### System Messages
+
+The model responds to different types of system prompts. Here are some examples:
+
+1. Basic prompt:
+```
+{"role": "system", "content": "You are a helpful assistant. Think before responding."}
+```
+
+2. Specific thought count:
+```
+{"role": "system", "content": "You are a helpful assistant. Think 3 thoughts before responding."}
+```
+
+3. Standard helper:
+```
+{"role": "system", "content": "You are a helpful assistant."}
+```
+
+About 40% of training examples include system messages, and 75% of those specifically mention thinking. This helps the model learn when and how much to think through problems.
+
+## Technical Details
+
+- **Base Model**: Llama 3.2 3B
+- **Training Data**: 2,500 carefully selected examples, each with up to 6 levels of thought chains
+- **Thought Selection**: At each level, the model generates multiple possible thoughts and picks the best one using an external ranking system
+
+## What's It Good For?
+
+This model excels at tasks that benefit from careful thinking:
+
+✅ Breaking down complex problems
+✅ Step-by-step math solutions
+✅ Detailed analysis of situations
+✅ Explaining complicated concepts
+✅ Making well-reasoned decisions
+
+## Limitations
+
+- Can sometimes overthink simple problems
+- Limited by the capabilities of the base Llama 3.2 3B model
+- Not suitable for critical decisions without human oversight
+- May occasionally generate irrelevant thought chains
+
+## Example Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("ericflo/Llama-3.2-3B-COT-v2")
+tokenizer = AutoTokenizer.from_pretrained("ericflo/Llama-3.2-3B-COT-v2")
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant. Think 3 thoughts before responding."},
+    {"role": "user", "content": "How would you teach a child to ride a bike?"}
+]
+
+input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt")
+output = model.generate(input_ids, temperature=1.0)
+response = tokenizer.decode(output[0])
+```
+
+Example output:
+```
+<thoughts>
+<thought>Safety should be the first priority - helmet and protective gear</thought>
+<thought>Starting with balance using training wheels can build confidence</thought>
+<thought>Breaking the process into small, manageable steps will help avoid overwhelm</thought>
+</thoughts>
+
+Here's how I would teach a child to ride a bike...
+[detailed answer follows]
+```
+
+## Citation
+
+```bibtex
+@misc{thought-ranked-llama-v2,
+  title={Thought-Ranked Llama 3.2 v2: Hierarchical Chain-of-Thought Generation},
+  author={[Eric Florenzano]},
+  year={2024},
+  howpublished={\url{https://huggingface.co/ericflo/Llama-3.2-3B-COT-v2}}
+}
+```
+
+## Acknowledgments
+
+This model builds on the Llama 3.2 3B base model from Meta. Special thanks to the open-source AI community for their contributions to chain-of-thought prompting techniques.