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---
language:
- en
license: apache-2.0
tags:
- merge
datasets:
- Locutusque/inst_mix_v2_top_100k
pipeline_tag: text-generation
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
model-index:
- name: LocutusqueXFelladrin-TinyMistral248M-Instruct
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: 24.74
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/LocutusqueXFelladrin-TinyMistral248M-Instruct
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: 27.79
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/LocutusqueXFelladrin-TinyMistral248M-Instruct
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: 26.12
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/LocutusqueXFelladrin-TinyMistral248M-Instruct
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: 40.12
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/LocutusqueXFelladrin-TinyMistral248M-Instruct
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: 49.09
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/LocutusqueXFelladrin-TinyMistral248M-Instruct
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: 0.0
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/LocutusqueXFelladrin-TinyMistral248M-Instruct
name: Open LLM Leaderboard
---
# 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.
# [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_Locutusque__LocutusqueXFelladrin-TinyMistral248M-Instruct)
| Metric |Value|
|---------------------------------|----:|
|Avg. |27.98|
|AI2 Reasoning Challenge (25-Shot)|24.74|
|HellaSwag (10-Shot) |27.79|
|MMLU (5-Shot) |26.12|
|TruthfulQA (0-shot) |40.12|
|Winogrande (5-shot) |49.09|
|GSM8k (5-shot) | 0.00|
|