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Model: ajibawa-2023/Code-Mistral-7B
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---
language:
- en
license: apache-2.0
tags:
- code
- mathematics
datasets:
- ajibawa-2023/Code-290k-ShareGPT
- m-a-p/Code-Feedback
- microsoft/orca-math-word-problems-200k
- teknium/openhermes
model-index:
- name: Code-Mistral-7B
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: 64.59
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-7B
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: 85.29
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-7B
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: 65.0
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-7B
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: 54.64
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-7B
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: 82.24
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-7B
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: 68.08
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-7B
name: Open LLM Leaderboard
---
**Code-Mistral-7B**
This Model is trained on refined version of my dataset [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT).
Besides this it is trained on following datasets:
[Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback)
[orca-math-word-problems-200k](https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k)
[Openhermes](https://huggingface.co/datasets/teknium/openhermes)
The idea was to check how this Model will perform with both Code & Maths datasets. This model is very good with Coding.
Maths is still hit & miss but you can test out this model.
This Model is trained on massive datasets so the results are very good.
I have used ChatML prompt format.
Kindly note this is qLoRA version, a rare exception.
**GGUF & Exllama**
GGUF: [Link](https://huggingface.co/bartowski/Code-Mistral-7B-GGUF)
Exllama v2: [Link](https://huggingface.co/bartowski/Code-Mistral-7B-exl2)
Special Thanks to [Bartowski](https://huggingface.co/bartowski) for quantizing this model.
**Training:**
Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took almost 33 Hours. Axolotl codebase was used for training purpose.
Entire data is trained on Mistral.
**Example Prompt:**
This model uses **ChatML** prompt format.
```
<|im_start|>system
You are a helpful AI assistant.<|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**
**C++**
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/jcmEZSRX7s7-B_ZybWwwN.jpeg)
**Error Resolving**
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/iy89IxjiZXAY4Id-ieLg7.jpeg)
**Matrices**
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/zFfq9lBA63wQzy0tP3_hd.jpeg)
**Machine Learning**
![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/Nv8dCpNxRtJGkOuulKzmn.jpeg)
# [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_ajibawa-2023__Code-Mistral-7B)
| Metric |Value|
|---------------------------------|----:|
|Avg. |69.97|
|AI2 Reasoning Challenge (25-Shot)|64.59|
|HellaSwag (10-Shot) |85.29|
|MMLU (5-Shot) |65.00|
|TruthfulQA (0-shot) |54.64|
|Winogrande (5-shot) |82.24|
|GSM8k (5-shot) |68.08|

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"model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
"model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
"model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
"model.norm.weight": "pytorch_model-00003-of-00003.bin"
}
}

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special_tokens_map.json Normal file
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{
"bos_token": {
"content": "<s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"eos_token": {
"content": "</s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"pad_token": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"unk_token": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
}
}

91122
tokenizer.json Normal file

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tokenizer.model (Stored with Git LFS) Normal file

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46
tokenizer_config.json Normal file
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{
"add_bos_token": true,
"add_eos_token": false,
"add_prefix_space": true,
"added_tokens_decoder": {
"0": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "</s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"additional_special_tokens": [],
"bos_token": "<s>",
"chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You are a helpful assistant.' %}{% endif %}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{{'<|im_start|>system\n' + system_message + '<|im_end|>\n'}}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
"clean_up_tokenization_spaces": false,
"eos_token": "</s>",
"legacy": true,
"model_max_length": 32768,
"pad_token": "<unk>",
"padding_side": "right",
"sp_model_kwargs": {},
"spaces_between_special_tokens": false,
"tokenizer_class": "LlamaTokenizer",
"unk_token": "<unk>",
"use_default_system_prompt": false,
"use_fast": true
}