Instructions to use budecosystem/code-millenials-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use budecosystem/code-millenials-8b with Transformers:

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

pipe = pipeline("text-generation", model="budecosystem/code-millenials-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("budecosystem/code-millenials-8b")
model = AutoModelForCausalLM.from_pretrained("budecosystem/code-millenials-8b")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use budecosystem/code-millenials-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "budecosystem/code-millenials-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "budecosystem/code-millenials-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/budecosystem/code-millenials-8b

SGLang

How to use budecosystem/code-millenials-8b 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 "budecosystem/code-millenials-8b" \
    --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": "budecosystem/code-millenials-8b",
		"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 "budecosystem/code-millenials-8b" \
        --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": "budecosystem/code-millenials-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use budecosystem/code-millenials-8b with Docker Model Runner:
```
docker model run hf.co/budecosystem/code-millenials-8b
```

Model is appropriately named

by Koitenshin - opened Aug 30, 2025

Discussion

Koitenshin

Aug 30, 2025

•

edited Aug 30, 2025

It claimed to write me a guide to help me write the code, when it actually did neither.

I gave it step by step instructions on how to write the code.

I'm not sure what you trained it on, but it's lazy as f***.

jithinvgab

Bud org Sep 3, 2025

This is quite an old model. We recommend using the latest coding models. However, if you can share the prompts that you have tried, we can try it out and give you a feedback if it helps.

Koitenshin

Sep 4, 2025

I didn't even notice the upload date on the files, sorry.

My initial prompt told it how to perform Principal Component Analysis and breaks the instructions down into 7 steps.

It paraphrased my prompt and said "Here, I wrote you a guide on how to do it."

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