Instructions to use SenseLLM/ReflectionCoder-CL-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SenseLLM/ReflectionCoder-CL-7B with Transformers:

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

pipe = pipeline("text-generation", model="SenseLLM/ReflectionCoder-CL-7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("SenseLLM/ReflectionCoder-CL-7B")
model = AutoModelForCausalLM.from_pretrained("SenseLLM/ReflectionCoder-CL-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-CL-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SenseLLM/ReflectionCoder-CL-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-CL-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/SenseLLM/ReflectionCoder-CL-7B

SGLang

How to use SenseLLM/ReflectionCoder-CL-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-CL-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-CL-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-CL-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-CL-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use SenseLLM/ReflectionCoder-CL-7B with Docker Model Runner:
```
docker model run hf.co/SenseLLM/ReflectionCoder-CL-7B
```

Houxing Ren commited on May 28, 2024

Commit

f00d2a4

1 Parent(s): 5a49989

Update README.md

Browse files

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README.md +16 -9

README.md CHANGED Viewed

@@ -1,3 +1,11 @@
 ## ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation
 <p align="center">
@@ -18,17 +26,17 @@ ReflectionCoder is a novel approach that effectively leverages reflection sequen
 | Model | Checkpoint | Size | HumanEval (+) | MBPP (+) | License|
 |:-------|:------------|:------|:---------------|:----------|:--------|
-| ReflectionCoder-CL-7B   | 🤗 [HF Link](https://huggingface.co/SenseLM/ReflectionCoder-CL-7B) | 7B   | 75.0 (68.9)     | 72.2 (61.4)     | [Llama2](https://ai.meta.com/llama/license/) |
-| ReflectionCoder-CL-34B  | 🤗 [HF Link](https://huggingface.co/SenseLM/ReflectionCoder-CL-34B) | 34B  | 70.7 (66.5)     | 68.4 (56.6)     | [Llama2](https://ai.meta.com/llama/license/) |
-| ReflectionCoder-DS-6.7B | 🤗 [HF Link](https://huggingface.co/SenseLM/ReflectionCoder-DS-6.7B) | 6.7B | 80.5 (74.4)     | 81.5 (69.6)     | [DeepSeek](https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL) |
-| ReflectionCoder-DS-33B  | 🤗 [HF Link](https://huggingface.co/SenseLM/ReflectionCoder-DS-33B) | 33B  | 82.9 (76.8) | 84.1 (72.0) | [DeepSeek](https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL) |
 ## Datasets
 | Dataset           | Link           | License                                      |
 |:-------------------|:----------------|:----------------------------------------------|
-| ReflectionSeq-GPT | 🤗 [HF Link](https://huggingface.co/datasets/SenseLM/ReflectionSeq-GPT) | [License](LICENSE) |
-| ReflectionSeq-DS  | 🤗 [HF Link](https://huggingface.co/datasets/SenseLM/ReflectionSeq-DS) | [License](LICENSE) |
 ## How to Use
@@ -43,7 +51,7 @@ Your Instruction
 ```
 #### Inference Code
-Please refer to our GitHub Repo [need update](https://ai.meta.com/llama/license/) for more technical details.
 ## Citation
@@ -69,5 +77,4 @@ We thank the following amazing projects that truly inspired us:
 - [Evol-CodeAlpaca-v1](https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1)
 - [MagiCoder](https://github.com/ise-uiuc/magicoder/tree/main)
 - [EvalPlus](https://github.com/evalplus/evalplus)
-- [OpenCoderInterpreter](https://github.com/OpenCodeInterpreter/OpenCodeInterpreter/tree/main)

+---
+license: apache-2.0
+datasets:
+- SenseLLM/ReflectionSeq-GPT
+- SenseLLM/ReflectionSeq-DS
+language:
+- en
+---
 ## ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation
 <p align="center">
 | Model | Checkpoint | Size | HumanEval (+) | MBPP (+) | License|
 |:-------|:------------|:------|:---------------|:----------|:--------|
+| ReflectionCoder-CL-7B   | 🤗 [HF Link](https://huggingface.co/SenseLLM/ReflectionCoder-CL-7B) | 7B   | 75.0 (68.9)     | 72.2 (61.4)     | [Llama2](https://ai.meta.com/llama/license/) |
+| ReflectionCoder-CL-34B  | 🤗 [HF Link](https://huggingface.co/SenseLLM/ReflectionCoder-CL-34B) | 34B  | 70.7 (66.5)     | 68.4 (56.6)     | [Llama2](https://ai.meta.com/llama/license/) |
+| ReflectionCoder-DS-6.7B | 🤗 [HF Link](https://huggingface.co/SenseLLM/ReflectionCoder-DS-6.7B) | 6.7B | 80.5 (74.4)     | 81.5 (69.6)     | [DeepSeek](https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL) |
+| ReflectionCoder-DS-33B  | 🤗 [HF Link](https://huggingface.co/SenseLLM/ReflectionCoder-DS-33B) | 33B  | 82.9 (76.8) | 84.1 (72.0) | [DeepSeek](https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL) |
 ## Datasets
 | Dataset           | Link           | License                                      |
 |:-------------------|:----------------|:----------------------------------------------|
+| ReflectionSeq-GPT | 🤗 [HF Link](https://huggingface.co/datasets/SenseLLM/ReflectionSeq-GPT) | [License](LICENSE) |
+| ReflectionSeq-DS  | 🤗 [HF Link](https://huggingface.co/datasets/SenseLLM/ReflectionSeq-DS) | [License](LICENSE) |
 ## How to Use
 ```
 #### Inference Code
+Please refer to our [GitHub Repo](https://github.com/SenseLLM/ReflectionCoder) for more technical details.
 ## Citation
 - [Evol-CodeAlpaca-v1](https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1)
 - [MagiCoder](https://github.com/ise-uiuc/magicoder/tree/main)
 - [EvalPlus](https://github.com/evalplus/evalplus)
+- [OpenCoderInterpreter](https://github.com/OpenCodeInterpreter/OpenCodeInterpreter/tree/main)