Instructions to use aphoticshaman/deepseek-coder-v2-lite-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aphoticshaman/deepseek-coder-v2-lite-nf4 with Transformers:

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

pipe = pipeline("text-generation", model="aphoticshaman/deepseek-coder-v2-lite-nf4", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("aphoticshaman/deepseek-coder-v2-lite-nf4", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("aphoticshaman/deepseek-coder-v2-lite-nf4", trust_remote_code=True)
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use aphoticshaman/deepseek-coder-v2-lite-nf4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aphoticshaman/deepseek-coder-v2-lite-nf4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aphoticshaman/deepseek-coder-v2-lite-nf4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aphoticshaman/deepseek-coder-v2-lite-nf4

SGLang

How to use aphoticshaman/deepseek-coder-v2-lite-nf4 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 "aphoticshaman/deepseek-coder-v2-lite-nf4" \
    --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": "aphoticshaman/deepseek-coder-v2-lite-nf4",
		"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 "aphoticshaman/deepseek-coder-v2-lite-nf4" \
        --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": "aphoticshaman/deepseek-coder-v2-lite-nf4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use aphoticshaman/deepseek-coder-v2-lite-nf4 with Docker Model Runner:
```
docker model run hf.co/aphoticshaman/deepseek-coder-v2-lite-nf4
```

DeepSeek-Coder-V2-Lite-NF4

NF4 quantized DeepSeek-Coder-V2-Lite-Instruct for AIMO3 tool-integrated reasoning.

Key Specs

Spec	Value
Total Params	16B
Active Params	2.4B (MoE)
Context Length	128K
VRAM (NF4)	~10GB

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
import torch

bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch.bfloat16,
)

model = AutoModelForCausalLM.from_pretrained(
    "aphoticshaman/deepseek-coder-v2-lite-nf4",
    quantization_config=bnb_config,
    device_map="auto",
    trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained("aphoticshaman/deepseek-coder-v2-lite-nf4")

Author

Ryan J Cardwell (Archer Phoenix) - AIMO3 Competitor

Downloads last month: 16

Safetensors

Model size

16B params

Tensor type

F32

BF16

Model tree for aphoticshaman/deepseek-coder-v2-lite-nf4

Base model

deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct

Quantized

(64)

this model