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Model: shaw2037/Llama-3.2-3B-Instruct-Reasoning
Source: Original Platform

README.md

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+---
+library_name: transformers
+language:
+- en
+base_model:
+- meta-llama/Llama-3.2-3B-Instruct
+---
+
+# LLaMA 3B Instruct Reasoning Model
+
+This model is a **fine-tuned version of LLaMA 3B Instruct**, optimized for reasoning tasks such as step-by-step problem solving and logical question answering.
+
+The model was fine-tuned using **LoRA (PEFT)** and later merged into the base model to create a **fully standalone model**.
+
+---
+
+## Base Model
+
+- `meta-llama/Llama-3-3b-instruct`
+
+---
+
+## Model Details
+
+- **Architecture:** LLaMA 3B
+- **Fine-tuning method:** LoRA (merged)
+- **Task:** Causal Language Modeling
+- **Use case:** Reasoning / instruction-following
+
+---
+
+## Features
+
+- Improved step-by-step reasoning 
+- Better structured answers 
+- Enhanced instruction following
+- Suitable for logical tasks
+
+---
+## Training Details
+
+This model was fine-tuned on a reasoning dataset from Hugging Face using LoRA.
+
+The LoRA weights were merged with the base model to produce a standalone model for easier deployment and usage.
+
+## How to Use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "shaw2037/Llama-3.2-3B-Instruct-Reasoning"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="auto"
+)
+
+prompt = "Solve step by step: If 2x + 3 = 11, what is x?"
+
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=200,
+    
+)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+
+
+## Limitations
+May produce incorrect reasoning steps.
+
+Can hallucinate in complex scenarios.
+
+Not guaranteed to be mathematically perfect.
+
+
+## Intended Use
+
+## Suitable for:
+
+reasoning experiments
+
+educational projects
+
+LLM research
+
+
+## Not suitable for:
+
+medical advice
+
+legal advice
+
+financial decisions
+
+safety-critical applications
+
+
+### Install dependencies
+
+```bash
+pip install transformers accelerate torch