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

Libraries

How to use SenseLLM/ReflectionCoder-DS-6.7B with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("SenseLLM/ReflectionCoder-DS-6.7B")
model = AutoModelForCausalLM.from_pretrained("SenseLLM/ReflectionCoder-DS-6.7B")
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 SenseLLM/ReflectionCoder-DS-6.7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SenseLLM/ReflectionCoder-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": "SenseLLM/ReflectionCoder-DS-6.7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/SenseLLM/ReflectionCoder-DS-6.7B

SGLang

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

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

ReflectionCoder-DS-6.7B / tokenizer_config.json

renhouxing

add chat template

1fbe5b3 almost 2 years ago

raw

history blame contribute delete

6.39 kB

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	"add_eos_token": false,
	"added_tokens_decoder": {
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	"additional_special_tokens": [
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	"<\|assistant\|>",
	"<\|text\|>",
	"<\|code\|>",
	"<\|execution\|>",
	"<\|endofblock\|>",
	"<\|endofmessage\|>"
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	"use_default_system_prompt": false,
	"chat_template": "{% for message in messages %}{% if message['role'] == 'user' %}{{ '<\|user\|>' }}{% elif message['role'] == 'system' %}{{ '<\|system\|>' }}{% elif message['role'] == 'assistant' %}{{ '<\|assistant\|>' }}{% endif %}{% if message['content'] is string %}{{ '<\|text\|>' + message['content'] + '<\|endofblock\|>' }}{% elif obj is sequence %}{% for block in message['content'] %}{% if block['type'] == 'text' %}{{ '<\|text\|>' }}{% elif block['type'] == 'code' %}{{ '<\|code\|>' }}{% elif block['type'] == 'execution' %}{{ '<\|execution\|>' }}{% endif %}{{ block['content'] + '<\|endofblock\|>' }}{% endfor %}{% endif %}{{ '<\|endofmessage\|>' }}{% endfor %}{% if add_generation_prompt %}{{ '<\|assistant\|>' }}{% endif %}"
	}