transformers safetensors mistral text-generation conversational en dataset:NeuralNovel/Neural-Story-v1 base_model:mistralai/Mistral-7B-Instruct-v0.2 license:apache-2.0 autotrain_compatible text-generation-inference 4-bit awq region:us
---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- NeuralNovel/Neural-Story-v1
library_name: transformers
inference: false
language:
- en
---

![Neural-Story](https://i.ibb.co/JFRYk6g/OIG-27.jpg)
# NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
[GGUF FILES HERE](https://huggingface.co/Kquant03/Mistral-7B-Instruct-v0.2-Neural-Story-GGUF)


The **Mistral-7B-Instruct-v0.2-Neural-Story** model, developed by NeuralNovel and funded by Techmind, is a language model finetuned from Mistral-7B-Instruct-v0.2.

Designed to generate instructive and narrative text, with a specific focus on storytelling.
This fine-tune has been tailored to provide detailed and creative responses in the context of narrative and optimised for short story telling.

Based on mistralAI, with apache-2.0 license, suitable for commercial or non-commercial use.

### Data-set
The model was finetuned using the Neural-Story-v1 dataset.

### Benchmark
| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | **64.96**   |
| ARC          | 64.08          |
| HellaSwag    | **66.89**   |
| MMLU         | 60.67         |
| TruthfulQA    | 66.89   |
| Winogrande    | **75.85**   |
| GSM8K         | 38.29        |

Evaluated on **HuggingFaceH4/open_llm_leaderboard**

### Summary

Fine-tuned with the intention of generating creative and narrative text, making it more suitable for creative writing prompts and storytelling.

#### Out-of-Scope Use

The model may not perform well in scenarios unrelated to instructive and narrative text generation. Misuse or applications outside its designed scope may result in suboptimal outcomes.

### Bias, Risks, and Limitations

The model may exhibit biases or limitations inherent in the training data. It is essential to consider these factors when deploying the model to avoid unintended consequences.

While the Neural-Story-v0.1 dataset serves as an excellent starting point for testing language models, users are advised to exercise caution, as there might be some inherent genre or writing bias.

### Hardware and Training


```

  n_epochs = 3,
  n_checkpoints = 3,
  batch_size = 12,
  learning_rate = 1e-5,



```

*Sincere appreciation to Techmind for their generous sponsorship.*