---
license: apache-2.0
tags:
- merge
- mergekit
- EmbeddedLLM/Mistral-7B-Merge-14-v0.1
- OpenPipe/mistral-ft-optimized-1218
---

# RLM-mini

RLM-mini is a 7.2 Billion parameter model,RLM-mini is designed to provide a robust and versatile natural language processing (NLP) capability, leveraging the strengths of two foundational models. By combining models from different sources, RLM-mini aims to inherit diverse linguistic features and training data nuances, resulting in improved performance across a wide range of NLP tasks. This includes more robust understanding and generation capabilities, especially in handling nuanced and context-heavy queries. The fine-tuning process integrates the best practices and optimizations from both parent models. This ensures that RLM-mini not only maintains high accuracy but also delivers responses more efficiently.

### Two Merged Models
* [EmbeddedLLM/Mistral-7B-Merge-14-v0.1](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.1)
* [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218)

# Usage

``` python

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("rudrashah/RLM-mini")
model = AutoModelForCausalLM.from_pretrained("rudrashah/RLM-mini")

input_token = tokenizer("How to make Pav Bhaji?", return_tensors="pt")
output = model.generate(**input_token, max_length=250)
output = tokenizer.decode(output[0])

```