Instructions to use mrm8488/phi-2-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mrm8488/phi-2-coder with Transformers:

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

pipe = pipeline("text-generation", model="mrm8488/phi-2-coder", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("mrm8488/phi-2-coder", trust_remote_code=True, dtype="auto")

MLX

How to use mrm8488/phi-2-coder with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm
# if on a CUDA device, also pip install mlx[cuda]

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("mrm8488/phi-2-coder")

prompt = "Once upon a time in"
text = generate(model, tokenizer, prompt=prompt, verbose=True)

Inference
Notebooks
Google Colab
Kaggle
Local Apps
LM Studio

vLLM

How to use mrm8488/phi-2-coder with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mrm8488/phi-2-coder"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrm8488/phi-2-coder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mrm8488/phi-2-coder

SGLang

How to use mrm8488/phi-2-coder 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 "mrm8488/phi-2-coder" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrm8488/phi-2-coder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "mrm8488/phi-2-coder" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrm8488/phi-2-coder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

MLX LM

How to use mrm8488/phi-2-coder with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Generate some text
mlx_lm.generate --model "mrm8488/phi-2-coder" --prompt "Once upon a time"

Docker Model Runner
How to use mrm8488/phi-2-coder with Docker Model Runner:
```
docker model run hf.co/mrm8488/phi-2-coder
```

mrm8488 commited on Dec 24, 2023

Commit

1bfb00d

1 Parent(s): 9d288cc

Update README.md

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@@ -11,14 +11,14 @@ model-index:
 license: apache-2.0
 language:
 - code
-thumbnail: https://huggingface.co/mrm8488/llama-2-coder-7b/resolve/main/llama2-coder-logo-removebg-preview.png
 datasets:
 - HuggingFaceH4/CodeAlpaca_20K
 pipeline_tag: text-generation
 ---
 <div style="text-align:center;width:250px;height:250px;">
-    <img src="https://huggingface.co/mrm8488/llama-2-coder-7b/resolve/main/llama2-coder-logo-removebg-preview.png" alt="llama-2 coder logo"">
 </div>

 license: apache-2.0
 language:
 - code
+thumbnail: https://huggingface.co/mrm8488/phi-2-coder/resolve/main/phi-2-coder-logo.png
 datasets:
 - HuggingFaceH4/CodeAlpaca_20K
 pipeline_tag: text-generation
 ---
 <div style="text-align:center;width:250px;height:250px;">
+    <img src="https://huggingface.co/mrm8488/phi-2-coder/resolve/main/phi-2-coder-logo.png" alt="phi-2 coder logo"">
 </div>