README.md

---
license: apache-2.0
datasets:
- databricks/databricks-dolly-15k
pipeline_tag: text-generation
model-index:
- name: Instruct_Mixtral-8x7B-v0.1_Dolly15K
  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: 69.28
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
      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: 87.59
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
      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: 70.96
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
      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: 64.83
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
      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: 82.56
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
      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: 59.44
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
      name: Open LLM Leaderboard
---
# Instruct_Mixtral-8x7B-v0.1_Dolly15K
Fine-tuned from Mixtral-8x7B-v0.1， used Dolly15k for the dataset. 85% for training, 14.9% validation, 0.1% test.  Trained for 1.0 epochs using QLora.  Trained with 1024 context window.

# Model Details
* **Trained by**: trained by [Brillibits](https://www.youtube.com/@Brillibits).
* **Model type:**  **Instruct_Mixtral-8x7B-v0.1_Dolly15K** is an auto-regressive language model based on the Llama 2 transformer architecture.
* **Language(s)**: English
* **License for Instruct_Mixtral-8x7B-v0.1_Dolly15K**: apache-2.0 license


# Prompting

## Prompt Template With Context

```
Write a 10-line poem about a given topic

Input:

The topic is about racecars

Output:
```
## Prompt Template Without Context
```
Who was the was the second president of the United States?

Output:
```

## Professional Assistance
This model and other models like it are great, but where LLMs hold the most promise is when they are applied on custom data to automate a wide variety of tasks

If you have a dataset and want to see if you might be able to apply that data to automate some tasks, and you are looking for professional assistance, contact me [here](mailto:[email protected])
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Brillibits__Instruct_Mixtral-8x7B-v0.1_Dolly15K)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |72.44|
|AI2 Reasoning Challenge (25-Shot)|69.28|
|HellaSwag (10-Shot)              |87.59|
|MMLU (5-Shot)                    |70.96|
|TruthfulQA (0-shot)              |64.83|
|Winogrande (5-shot)              |82.56|
|GSM8k (5-shot)                   |59.44|