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Model: ajibawa-2023/Code-Llama-3-8B Source: Original Platform
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README.md
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README.md
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---
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license: llama3
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datasets:
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- ajibawa-2023/Code-290k-ShareGPT
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- m-a-p/CodeFeedback-Filtered-Instruction
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- m-a-p/Code-Feedback
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- microsoft/orca-math-word-problems-200k
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language:
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- en
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tags:
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- code
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- Python
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- Cpp
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- PHP
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- JS
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- Java
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- Rust
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- Ruby
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- SQL
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- MySql
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- R
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- Julia
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---
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**Code-Llama-3-8B**
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This Model is trained on refined version of my dataset [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT).
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Besides this it is trained on following datasets:
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[Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback)
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[orca-math-word-problems-200k](https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k)
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[CodeFeedback-Filtered-Instruction](https://huggingface.co/datasets/m-a-p/CodeFeedback-Filtered-Instruction)
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The idea was to check how this Model will perform with both Code & Maths datasets. This model is very good with Coding.
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Maths outputs are also very good. You can test out this model.
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It is very very good in Code generation in various languages such as **Python, Java, JavaScript, GO, C++, Rust, Ruby, Sql, MySql, R, Julia, Haskell**, etc..
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This model will also generate detailed explanation/logic behind each code.
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This Model is trained on massive datasets so the results are very good. You can check the Examples given below.
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I have used ChatML prompt format.
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This is Fully Finetuned Model.
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**GGUF & Exllama**
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GGUF: [Link](https://huggingface.co/bartowski/Code-Llama-3-8B-GGUF)
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Exllama v2: [Link](https://huggingface.co/bartowski/Code-Llama-3-8B-exl2)
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Special Thanks to [Bartowski](https://huggingface.co/bartowski) for quantizing this model.
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**Training:**
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Entire dataset was trained on 4 x A100 80GB. For 2 epoch, training took more than 160 Hours. Axolotl & Deepspeed codebase was used for training purpose.
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Entire data is trained on Llama-3-8B by Meta.
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**Example Prompt:**
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This model uses **ChatML** prompt format.
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```
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<|im_start|>system
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You are a helpful Coding assistant.<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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```
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You can modify above Prompt as per your requirement.
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One example will be:
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```
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This is a conversation with your helpful Coding assistant. Assistant can generate Code in various Programming Languages along with necessary explanation.
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```
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I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
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Thank you for your love & support.
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**Example Output**
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Example 1
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Example 2
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Example 3
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Example 4
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Example 5
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config.json
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"_name_or_path": "/home/feynmla100/Downloads/Llama-3-8B/",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"model_type": "llama",
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"rope_scaling": null,
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.40.0.dev0",
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"use_cache": false,
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"vocab_size": 128256
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}
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23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
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|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
410562
tokenizer.json
Normal file
410562
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2063
tokenizer_config.json
Normal file
2063
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user