Instructions to use mrcuddle/Python-Qwen2.5-Coder-3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mrcuddle/Python-Qwen2.5-Coder-3B-Instruct with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mrcuddle/Python-Qwen2.5-Coder-3B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mrcuddle/Python-Qwen2.5-Coder-3B-Instruct")
model = AutoModelForCausalLM.from_pretrained("mrcuddle/Python-Qwen2.5-Coder-3B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

PEFT
How to use mrcuddle/Python-Qwen2.5-Coder-3B-Instruct with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use mrcuddle/Python-Qwen2.5-Coder-3B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mrcuddle/Python-Qwen2.5-Coder-3B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrcuddle/Python-Qwen2.5-Coder-3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mrcuddle/Python-Qwen2.5-Coder-3B-Instruct

SGLang

How to use mrcuddle/Python-Qwen2.5-Coder-3B-Instruct with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "mrcuddle/Python-Qwen2.5-Coder-3B-Instruct" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrcuddle/Python-Qwen2.5-Coder-3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "mrcuddle/Python-Qwen2.5-Coder-3B-Instruct" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrcuddle/Python-Qwen2.5-Coder-3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mrcuddle/Python-Qwen2.5-Coder-3B-Instruct with Docker Model Runner:
```
docker model run hf.co/mrcuddle/Python-Qwen2.5-Coder-3B-Instruct
```

Python-Qwen2.5-Coder-3B-Instruct

File size: 1,362 Bytes

4a8739b

{
    "model": "Qwen/Qwen2.5-Coder-3B-Instruct",
    "project_name": "autotrain-0i76d-sriaf",
    "data_path": "mrcuddle/python-instruct-alpaca",
    "train_split": "train",
    "valid_split": null,
    "add_eos_token": true,
    "block_size": 1024,
    "model_max_length": 2048,
    "padding": "right",
    "trainer": "sft",
    "use_flash_attention_2": false,
    "log": "tensorboard",
    "disable_gradient_checkpointing": false,
    "logging_steps": -1,
    "eval_strategy": "epoch",
    "save_total_limit": 1,
    "auto_find_batch_size": true,
    "mixed_precision": "fp16",
    "lr": 3e-05,
    "epochs": 3,
    "batch_size": 2,
    "warmup_ratio": 0.1,
    "gradient_accumulation": 4,
    "optimizer": "adamw_torch",
    "scheduler": "linear",
    "weight_decay": 0.0,
    "max_grad_norm": 1.0,
    "seed": 42,
    "chat_template": "none",
    "quantization": "int4",
    "target_modules": "all-linear",
    "merge_adapter": true,
    "peft": true,
    "lora_r": 16,
    "lora_alpha": 32,
    "lora_dropout": 0.05,
    "model_ref": null,
    "dpo_beta": 0.1,
    "max_prompt_length": 128,
    "max_completion_length": null,
    "prompt_text_column": "prompt",
    "text_column": "conversation",
    "rejected_text_column": "rejected_text",
    "push_to_hub": true,
    "username": "mrcuddle",
    "unsloth": false,
    "distributed_backend": "deepspeed"
}