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---
base_model: EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
license: apache-2.0
language:
- en
---
This is a reasoning and reflect instruction-tuned generative model in 3B size (text in/text out).
**Model Architecture:**
Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) with GRPO fine tuning using unsloth, to align with human preferences for helpfulness and safety.
Fine tune with Numina math dataset.
### Use with transformers
Starting with `transformers >= 4.43.0` onward, you can run conversational inference using the Transformers `pipeline` abstraction or by leveraging the Auto classes with the `generate()` function.
Make sure to update your transformers installation via `pip install --upgrade transformers`.
```python
import torch
from transformers import pipeline
model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-ThinkMath"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype=torch.bfloat16,
device_map="auto",
)
messages = [
{"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
{"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
messages,
max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
```
## Using [SuperTransformer](https://github.com/tomtyiu/SuperTransformer-SHF)
```python
import SuperTransformer
# Load SuperTransformer Class, (1) Loads Huggingface model, (2) System Prompt (3) Text/prompt (4)Max tokens
SuperTransformers = SuperTransformers("EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-ThinkMath","You are a highly knowledgeable assistant with expertise in mathematics. <reasoning>...</reasoning><reflecting>...</reflecting><answer>...</answer>","What is the area of a circle, radius=16, reason step by step", 2026)
# 8-bit quantization
SuperTransformers.HuggingFaceTransformer8bit()
# or 4-bit quantization
SuperTransformers.HuggingFaceTransformer4bit()
```
# Uploaded model
- **Developed by:** EpistemeAI
- **License:** apache-2.0
- **Finetuned from model :** EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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