Instructions to use aigcode/AIGCodeGeek-DS-6.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aigcode/AIGCodeGeek-DS-6.7B with Transformers:

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

pipe = pipeline("text-generation", model="aigcode/AIGCodeGeek-DS-6.7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("aigcode/AIGCodeGeek-DS-6.7B")
model = AutoModelForCausalLM.from_pretrained("aigcode/AIGCodeGeek-DS-6.7B", device_map="auto")
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 Settings

vLLM

How to use aigcode/AIGCodeGeek-DS-6.7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aigcode/AIGCodeGeek-DS-6.7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aigcode/AIGCodeGeek-DS-6.7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aigcode/AIGCodeGeek-DS-6.7B

SGLang

How to use aigcode/AIGCodeGeek-DS-6.7B 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 "aigcode/AIGCodeGeek-DS-6.7B" \
    --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": "aigcode/AIGCodeGeek-DS-6.7B",
		"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 "aigcode/AIGCodeGeek-DS-6.7B" \
        --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": "aigcode/AIGCodeGeek-DS-6.7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use aigcode/AIGCodeGeek-DS-6.7B with Docker Model Runner:
```
docker model run hf.co/aigcode/AIGCodeGeek-DS-6.7B
```

Leon-Leee commited on Apr 26, 2024

Commit

cbafc7a

verified ·

1 Parent(s): 3b3be01

Update README.md

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README.md +5 -2

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@@ -17,8 +17,10 @@ tags:
 ### Introduction
 AIGCodeGeek-DS-6.7B is the first version of our Code-LLM family with competitive performance on benchmarks such as HumanEval(+) and MBPP(+).
 It gains a lot of insights from the open-source community and we deeply appreciate all of these great works.
-We are preparing for the tech report, so stay tuned for more details.
 ### Model Details
 #### Model Description
@@ -35,7 +37,8 @@ A mixture of both
 To check out our evaluation results: [EvalPlus](https://evalplus.github.io/leaderboard.html)
 ### Requirements
-It should work with the same requirements as DeepSeek-Coder-6.7B
 ```torch>=2.0
 tokenizers>=0.14.0
 transformers>=4.35.0

 ### Introduction
 AIGCodeGeek-DS-6.7B is the first version of our Code-LLM family with competitive performance on benchmarks such as HumanEval(+) and MBPP(+).
 It gains a lot of insights from the open-source community and we deeply appreciate all of these great works.
+We are preparing for the tech report, so stay tuned for more details:)
 ### Model Details
 #### Model Description
 To check out our evaluation results: [EvalPlus](https://evalplus.github.io/leaderboard.html)
 ### Requirements
+It should work with the same requirements as DeepSeek-Coder-6.7B or the following packages:
 ```torch>=2.0
 tokenizers>=0.14.0
 transformers>=4.35.0