transformers pytorch safetensors mistral text-generation merge en dataset:Locutusque/inst_mix_v2_top_100k license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- Locutusque/inst_mix_v2_top_100k
language:
- en
license: apache-2.0
pipeline_tag: text-generation
tags:
- merge
widget:
- text: '<|USER|> Design a Neo4j database and Cypher function snippet to Display Extreme
    Dental hygiene: Using Mouthwash for Analysis for Beginners. Implement if/else
    or switch/case statements to handle different conditions related to the Consent.
    Provide detailed comments explaining your control flow and the reasoning behind
    each decision. <|ASSISTANT|> '
- text: '<|USER|> Write me a story about a magical place. <|ASSISTANT|> '
- text: '<|USER|> Write me an essay about the life of George Washington <|ASSISTANT|> '
- text: '<|USER|> Solve the following equation 2x + 10 = 20 <|ASSISTANT|> '
- text: '<|USER|> Craft me a list of some nice places to visit around the world. <|ASSISTANT|> '
- text: '<|USER|> How to manage a lazy employee: Address the employee verbally. Don''t
    allow an employee''s laziness or lack of enthusiasm to become a recurring issue.
    Tell the employee you''re hoping to speak with them about workplace expectations
    and performance, and schedule a time to sit down together. Question: To manage
    a lazy employee, it is suggested to talk to the employee. True, False, or Neither?
    <|ASSISTANT|> '
inference:
  parameters:
    temperature: 0.5
    do_sample: true
    top_p: 0.5
    top_k: 30
    max_new_tokens: 250
    repetition_penalty: 1.15
---
# LocutusqueXFelladrin-TinyMistral248M-Instruct
This model was created by merging Locutusque/TinyMistral-248M-Instruct and Felladrin/TinyMistral-248M-SFT-v4 using mergekit. After the two models were merged, the resulting model was further trained on ~20,000 examples on the Locutusque/inst_mix_v2_top_100k at a low learning rate to further normalize weights. The following is the YAML config used to merge:

```yaml
models:
  - model: Felladrin/TinyMistral-248M-SFT-v4
    parameters:
      weight: 0.5
  - model: Locutusque/TinyMistral-248M-Instruct
    parameters:
      weight: 1.0
merge_method: linear
dtype: float16
```

The resulting model combines the best of both worlds. With Locutusque/TinyMistral-248M-Instruct's coding capabilities and reasoning skills, and Felladrin/TinyMistral-248M-SFT-v4's low hallucination and instruction-following capabilities. The resulting model has an incredible performance considering its size.

## Evaluation
Found in the Open LLM Leaderboard.