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

Libraries

How to use RedHatAI/phi-2-super-marlin with Transformers:

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

pipe = pipeline("text-generation", model="RedHatAI/phi-2-super-marlin", 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("RedHatAI/phi-2-super-marlin", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("RedHatAI/phi-2-super-marlin", trust_remote_code=True, 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 RedHatAI/phi-2-super-marlin with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RedHatAI/phi-2-super-marlin"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/phi-2-super-marlin",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/RedHatAI/phi-2-super-marlin

SGLang

How to use RedHatAI/phi-2-super-marlin 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 "RedHatAI/phi-2-super-marlin" \
    --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": "RedHatAI/phi-2-super-marlin",
		"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 "RedHatAI/phi-2-super-marlin" \
        --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": "RedHatAI/phi-2-super-marlin",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use RedHatAI/phi-2-super-marlin with Docker Model Runner:
```
docker model run hf.co/RedHatAI/phi-2-super-marlin
```

mgoin commited on Mar 2, 2024

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+---
+license: mit
+license_link: https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE
+language:
+- en
+widget:
+- text: Hello who are you?
+  example_title: Identity
+- text: What can you do?
+  example_title: Capabilities
+- text: Create a fastapi endpoint to retrieve the weather given a zip code.
+  example_title: Coding
+tags:
+- convAI
+- conversational
+pipeline_tag: text-generation
+inference: false
+---
+<!-- description start -->
+# Phi-2 Super (SFT + cDPO)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62ceeb27e7f6014c0e9d9268/5-LQCMrXi8FN_ewcWL47v.png)
+- **Model creator:** [Anton Bacaj](https://huggingface.co/abacaj)
+- **Original model:** [Phi-2 Super](https://huggingface.co/abacaj/phi-2-super)
+## Description
+This repo contains 4-bit Marlin format model files for [abacaj's Phi-2 Super](https://huggingface.co/abacaj/phi-2-super)
+### Phi-2-super (SFT + cDPO)
+Base Model: [microsoft/phi-2](https://huggingface.co/microsoft/phi-2)
+### Chat template
+The model uses the same chat template as found in Mistral instruct models:
+```python
+text = "<|endoftext|>[INST] What is your favourite condiment? [/INST]"
+"Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!<|endoftext|> "
+"[INST] Do you have mayonnaise recipes? [/INST]"
+```
+### MT-bench / heval
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62ceeb27e7f6014c0e9d9268/lnFu3x1ufdpQVysIrX4-G.png)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62ceeb27e7f6014c0e9d9268/mJfBpH8dIW7Ii2KAGI_A7.png)
+<!-- description end -->