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Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
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including but not limited to software source code, documentation
source, and configuration files.
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transformation or translation of a Source form, including but
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(b) You must cause any modified files to carry prominent notices stating
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(c) You must retain, in the Source form of the Licensed Material,
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5. Disclaimer of Warranty.
THE LICENSED MATERIAL IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND.
6. Limitation of Liability.
IN NO EVENT SHALL LICENSOR BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY ARISING FROM THE USE OF THE LICENSED MATERIAL.
END OF TERMS AND CONDITIONS
Copyright 2024 amkyawdev
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
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Unless required by applicable law or agreed to in writing, software
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See the License for the specific language governing permissions and
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---
pipeline_tag: text-generation
license: apache-2.0
tags:
- code-generation
- myanmar
- burmese
- qwen
- qwen2
- qwen2.5
- qwen2.5-coder
- transformers
- conversational
- text-generation
library_name: transformers
inference:
parameters:
max_new_tokens: 512
temperature: 0.2
top_p: 0.95
repetition_penalty: 1.1
model-index:
- name: amk-coder-v2
results:
- task:
type: text-generation
name: CodeGeneration
dataset:
name: HumanEval
type: openai/openai_humaneval
metrics:
- type: pass_at_1
value: 50
verified: false
- type: pass_at_10
value: 75
verified: false
- task:
type: text-generation
name: PythonCodeGeneration
dataset:
name: MBPP
type: abdshhayan/MBPP
metrics:
- type: pass_at_1
value: 55
verified: false
---
# 🤖 amk-coder-v2 — Myanmar Coding Agent
Myanmar Coding Assistant — Fine-tuned from **Qwen2.5-Coder-1.5B** using **LoRA (PEFT)**
![Model](https://img.shields.io/badge/Model-Size-2B-blue)
![License](https://img.shields.io/badge/License-Apache--2.0-green)
![HuggingFace](https://img.shields.io/badge/-HuggingFace-orange)
---
## 📋 Table of Contents
- [Model Overview](#model-overview)
- [Training Details](#training-details)
- [Quick Start](#quick-start)
- [Usage Examples](#usage-examples)
- [API Deployment](#api-deployment)
- [Limitations](#limitations)
- [License](#license)
---
## Model Overview
**amk-coder-v2** is a Myanmar-localized coding assistant fine-tuned from **Qwen2.5-Coder-1.5B** using LoRA (PEFT) technique.
| Attribute | Value |
|---|---|
| **Base Model** | Qwen2.5-Coder-1.5B |
| **Parameters** | 2B (2,000M) |
| **Architecture** | Qwen2ForCausalLM |
| **Training Method** | LoRA (PEFT) fine-tuning |
| **Dataset** | [amkyawdev/mm-llm-coder-agent-dataset](https://huggingface.co/datasets/amkyawdev/mm-llm-coder-agent-dataset) (4M rows) |
| **Context Length** | 32,768 tokens |
| **Format** | Safetensors (BF16) |
| **License** | Apache-2.0 |
| **Languages** | Burmese + English |
### Features
| Feature | Description |
|---|---|
| 🇲🇲 **Myanmar Support** | Full support for Myanmar Unicode text |
| 💻 **Code Generation** | Python, JavaScript, C++, Java, and more |
| 🐛 **Debugging** | Bug detection and fixes |
| 📖 **Code Explanation** | Line-by-line explanations |
---
## Training Details
| Parameter | Value |
|---|---|
| **Framework** | Transformers + PEFT |
| **Training Method** | LoRA fine-tuning |
| **Target Modules** | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
| **Optimizer** | paged_adamw_8bit |
| **Learning Rate** | 3e-5 |
| **Epochs** | 3 |
| **Batch Size** | 8 |
| **Max Length** | 2048 |
| **Precision** | FP16 mixed |
| **Hardware** | Kaggle Dual T4 GPU |
| **Training Time** | ~3-5 hrs |
### Chat Template (ChatML)
```
<|im_start|>system
You are an expert Myanmar AI coding agent with tool access.<|im_end|>
<|im_start|>user
{Instruction}
Tools available: {Tools}<|im_end|>
<|im_start|>assistant
Thought & Code:
```
---
## Quick Start
### Using Transformers (Python)
```python
# Method 1: Pipeline (Recommended for beginners)
from transformers import pipeline
pipe = pipeline("text-generation", model="amkyawdev/amk-coder-v2")
messages = [
{"role": "user", "content": "Python function တစ်ခုရေးပါ။ list comprehension နဲ့ sorting လုပ်ပေးပါ။"}
]
result = pipe(messages, max_new_tokens=512, temperature=0.2)
print(result[0]['generated_text'])
# Method 2: Direct Model Loading
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("amkyawdev/amk-coder-v2")
model = AutoModelForCausalLM.from_pretrained(
"amkyawdev/amk-coder-v2",
torch_dtype=torch.bfloat16,
device_map="auto"
)
messages = [
{"role": "system", "content": "You are a helpful coding assistant."},
{"role": "user", "content": "Write a Python function to reverse a string"}
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
return_tensors="pt"
).to(model.device)
outputs = model.generate(inputs, max_new_tokens=512, temperature=0.2)
response = tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True)
print(response)
```
### Using vLLM (Production)
```bash
# Install vLLM
pip install vllm
# Start server
vllm serve "amkyawdev/amk-coder-v2" --tensor-parallel-size 1
# API call
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
-d '{
"model": "amkyawdev/amk-coder-v2",
"messages": [
{"role": "user", "content": "Hello, write Python code"}
],
"max_tokens": 512,
"temperature": 0.2
}'
```
### Using SGLang
```bash
# Install SGLang
pip install sglang
# Start server
python -m sglang.launch_server --model-path "amkyawdev/amk-coder-v2" --port 30000
# API call
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
-d '{
"model": "amkyawdev/amk-coder-v2",
"messages": [{"role": "user", "content": "Write a hello world in Python"}]
}'
```
---
## Usage Examples
### 🇲🇲 Myanmar Prompts
```python
messages = [
{"role": "user", "content": "Python function တစ်ခုရေးပါ။ ဂဏန်းတွေကို sorting လုပ်ပေးပါ။"}
]
# Output: def sort_numbers(numbers): return sorted(numbers)
```
### 🇬🇧 English Prompts
```python
messages = [
{"role": "user", "content": "Explain this code:\nfor i in range(10):\n print(i)"}
]
# Output: This is a for loop that prints numbers 0 to 9
```
### 🐛 Debugging
```python
messages = [
{"role": "user", "content": "Fix this Python code:\nprint('Hello' + 5)"}
]
# Output: TypeError fix suggestion with corrected code
```
---
## API Deployment
### Backend Server
```bash
cd backend
pip install -r requirements.txt
export HF_TOKEN=hf_your_token
uvicorn app.main:app --host 0.0.0.0 --port 8000
```
### Endpoints
| Method | Endpoint | Description |
|---|---|---|
| GET | `/` | Health check |
| GET | `/health` | Service health status |
| POST | `/chat` | Streaming chat (SSE) |
| GET | `/demo` | Demo HTML interface |
| GET | `/models` | Model information |
### Request Format
```bash
# Streaming chat
curl -X POST "http://localhost:8000/chat" \
-H "Content-Type: application/json" \
-d '{
"messages": [
{"role": "user", "content": "Write a Fibonacci function in Python"}
],
"stream": true
}'
```
### Docker Deployment
```bash
# Using Docker Model Runner
docker model run hf.co/amkyawdev/amk-coder-v2
# Using vLLM Docker
docker run --gpus all \
-v ~/.cache/huggingface:/root/.cache/huggingface \
-p 8000:8000 \
--rm \
vllm/vllm-openai:latest \
--model amkyawdev/amk-coder-v2
```
---
## ⚠️ Limitations
1. **Context Length** - Maximum 32,768 tokens
2. **Code Quality** - May generate incorrect code; verify outputs
3. **Myanmar Unicode** - Best results with proper Zawgyi-to-Unicode conversion
4. **Domain Knowledge** - Limited to common programming languages
5. **Safety** - May produce harmful content; use responsible AI practices
---
## 📖 Resources
- [Qwen2.5-Coder Documentation](https://qwenlm.github.io/blog/Qwen2.5-Coder/)
- [Transformers Library](https://huggingface.co/docs/transformers)
- [HuggingFace Hub](https://huggingface.co/amkyawdev/amk-coder-v2)
---
## 🙏 Acknowledgments
- **Alibaba Cloud Qwen Team** - Base model Qwen2.5-Coder
- **HuggingFace** - Model hosting and infrastructure
- **Myanmar Developer Community** - Testing and feedback
---
## 📝 License
Apache License 2.0 - See LICENSE file for details.
---
## 📧 Contact
- **Author**: amkyawdev
- **HuggingFace**: [amkyawdev/amk-coder-v2](https://huggingface.co/amkyawdev/amk-coder-v2)
- **GitHub**: [github.com/amkyawdev](https://github.com/amkyawdev)
---
*Made with ❤️ for Myanmar Developers*

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{%- if messages[0]['role'] == 'system' %}
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
{%- else %}
{{- '<|im_start|>system\nYou are amk-coder-v2, a helpful Myanmar coding assistant. Respond in the same language as the user (Myanmar or English). Provide clean, well-commented code. Explain code when helpful.<|im_end|>\n' }}
{%- endif %}
{%- for message in messages %}
{%- if message.role == 'user' %}
{{- '<|im_start|>user\n' + message.content + '<|im_end|>\n' }}
{%- elif message.role == 'assistant' %}
{{- '<|im_start|>assistant\n' + message.content + '<|im_end|>\n' }}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- endif %}

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{
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 151643,
"dtype": "float16",
"eos_token_id": 151643,
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 8960,
"max_position_embeddings": 32768,
"model_type": "qwen2",
"num_attention_heads": 12,
"num_hidden_layers": 28,
"num_key_value_heads": 2,
"pad_token_id": 151643,
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 1000000.0,
"sliding_window": null,
"tie_word_embeddings": true,
"transformers_version": "4.45.0",
"use_cache": true,
"vocab_size": 151936
}

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{
"bos_token_id": 151643,
"eos_token_id": 151643,
"pad_token_id": 151643,
"max_new_tokens": 512,
"do_sample": true,
"temperature": 0.2,
"top_p": 0.95,
"repetition_penalty": 1.1
}

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{
"add_bos_token": false,
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": null,
"clean_up_tokenization_spaces": false,
"eos_token": "<|endoftext|>",
"errors": "replace",
"extra_special_tokens": [
"<|im_start|>",
"<|im_end|>",
"<|object_ref_start|>",
"<|object_ref_end|>",
"<|box_start|>",
"<|box_end|>",
"<|quad_start|>",
"<|quad_end|>",
"<|vision_start|>",
"<|vision_end|>",
"<|vision_pad|>",
"<|image_pad|>",
"<|video_pad|>"
],
"is_local": false,
"model_max_length": 32768,
"pad_token": "<|endoftext|>",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null,
"chat_template": "{%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n{%- else %}\n {{- '<|im_start|>system\\nYou are amk-coder-v2, a helpful Myanmar coding assistant. Respond in the same language as the user (Myanmar or English). Provide clean, well-commented code. Explain code when helpful.<|im_end|>\\n' }}\n{%- endif %}\n{%- for message in messages %}\n {%- if message.role == 'user' %}\n {{- '<|im_start|>user\\n' + message.content + '<|im_end|>\\n' }}\n {%- elif message.role == 'assistant' %}\n {{- '<|im_start|>assistant\\n' + message.content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n"
}