Total runs:
256
Run Growth:
92
Growth Rate:
35.94%
Sponsored by
Vmake Labs Video Enhancer
ajibawa-2023 / WikiHow-Mistral-Instruct-7B
Model's Last Updated: April 07 2024
text-generation
Introduction of WikiHow-Mistral-Instruct-7B
Model Details of WikiHow-Mistral-Instruct-7B
WikiHow-Mistral-Instruct-7B
This Model is trained on my WikiHow dataset.
This model is very very good with generating tutorials in the style of WikiHow . By leveraging this repository of practical knowledge, the model has been trained to comprehend and generate text that is highly informative and instructional in nature. The depth and accuracy of generated tutorials is exceptional. The WikiHow dataset encompasses a wide array of topics, ranging from everyday tasks to specialized skills, making it an invaluable resource for refining the capabilities of language models. Through this fine-tuning process, the model has been equipped with the ability to offer insightful guidance and assistance across diverse domains.
This is a fully finetuned model. Links for Quantized models are given below.
GGUF & Exllama
GGUF: Link
Exllama v2: Link
Special Thanks to Bartowski for quantizing this model.
Training:
Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took more than 15 Hours. Axolotl codebase was used for training purpose. Entire data is trained on Mistral-7B-Instruct-v0.2.
Example Prompt:
This model uses ChatML prompt format.
<|im_start|>system
You are a Helpful Assistant who can write long and very detailed tutorial on various subjects in the styles of WiKiHow. Include in depth explanations for each step and how it helps achieve the desired outcome, including key tips and guidelines.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
You can modify above Prompt as per your requirement.
I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
Thank you for your love & support.
Example Output
Example 1
Example 2
Example 3
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 61.25 |
| AI2 Reasoning Challenge (25-Shot) | 60.92 |
| HellaSwag (10-Shot) | 80.99 |
| MMLU (5-Shot) | 58.57 |
| TruthfulQA (0-shot) | 62.16 |
| Winogrande (5-shot) | 74.82 |
| GSM8k (5-shot) | 30.02 |
Runs of ajibawa-2023 WikiHow-Mistral-Instruct-7B on huggingface.co
73
Total runs
-1
24-hour runs
-2
3-day runs
-6
7-day runs
-17
30-day runs
More Information About WikiHow-Mistral-Instruct-7B huggingface.co Model
Url of WikiHow-Mistral-Instruct-7B
WikiHow-Mistral-Instruct-7B huggingface.co Url
Provider of WikiHow-Mistral-Instruct-7B huggingface.co
Other API from ajibawa-2023
Updated:March 04 2024
Total runs:
208
Run Growth:
54
Growth Rate:
25.96%
Total runs:
204
Run Growth:
57
Growth Rate:
27.94%
Total runs:
192
Run Growth:
71
Growth Rate:
36.98%
Total runs:
130
Run Growth:
-843
Growth Rate:
-648.46%
Total runs:
109
Run Growth:
20
Growth Rate:
18.35%
Total runs:
97
Run Growth:
23
Growth Rate:
23.71%
Total runs:
86
Run Growth:
-4
Growth Rate:
-4.65%
Total runs:
80
Run Growth:
-12
Growth Rate:
-15.00%
Total runs:
76
Run Growth:
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Growth Rate:
-100.00%
Total runs:
75
Run Growth:
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Growth Rate:
-1.33%
Total runs:
70
Run Growth:
4
Growth Rate:
5.71%
Total runs:
65
Run Growth:
-4
Growth Rate:
-6.15%
Total runs:
64
Run Growth:
-5
Growth Rate:
-7.81%
Total runs:
64
Run Growth:
0
Growth Rate:
0.00%
Total runs:
54
Run Growth:
13
Growth Rate:
24.07%
Total runs:
39
Run Growth:
-2
Growth Rate:
-5.13%
Total runs:
35
Run Growth:
0
Growth Rate:
0.00%
Total runs:
33
Run Growth:
7
Growth Rate:
21.21%
Total runs:
30
Run Growth:
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Growth Rate:
-3.33%