---
language:
- en
license: apache-2.0
library_name: transformers
tags:
- llama-cpp
- gguf-my-repo
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- NeuralNovel/Neural-Story-v1
inference: false
model-index:
- name: Mistral-7B-Instruct-v0.2-Neural-Story
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 64.08
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 83.97
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 60.67
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 66.89
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 75.85
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 38.29
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
      name: Open LLM Leaderboard
---

# DavidAU/Mistral-7B-Instruct-v0.2-Neural-Story-Q4_K_M-GGUF
This model was converted to GGUF format from [`NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story`](https://huggingface.co/NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story) for more details on the model.
## Use with llama.cpp

Install llama.cpp through brew.

```bash
brew install ggerganov/ggerganov/llama.cpp
```
Invoke the llama.cpp server or the CLI.

CLI:

```bash
llama-cli --hf-repo DavidAU/Mistral-7B-Instruct-v0.2-Neural-Story-Q4_K_M-GGUF --model mistral-7b-instruct-v0.2-neural-story.Q4_K_M.gguf -p "The meaning to life and the universe is"
```

Server:

```bash
llama-server --hf-repo DavidAU/Mistral-7B-Instruct-v0.2-Neural-Story-Q4_K_M-GGUF --model mistral-7b-instruct-v0.2-neural-story.Q4_K_M.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

```
git clone https://github.com/ggerganov/llama.cpp &&             cd llama.cpp &&             make &&             ./main -m mistral-7b-instruct-v0.2-neural-story.Q4_K_M.gguf -n 128
```