Instructions to use dphn/dolphin-2.9-llama3-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dphn/dolphin-2.9-llama3-8b with Transformers:

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

pipe = pipeline("text-generation", model="dphn/dolphin-2.9-llama3-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("dphn/dolphin-2.9-llama3-8b")
model = AutoModelForCausalLM.from_pretrained("dphn/dolphin-2.9-llama3-8b", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use dphn/dolphin-2.9-llama3-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dphn/dolphin-2.9-llama3-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dphn/dolphin-2.9-llama3-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/dphn/dolphin-2.9-llama3-8b

SGLang

How to use dphn/dolphin-2.9-llama3-8b 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 "dphn/dolphin-2.9-llama3-8b" \
    --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": "dphn/dolphin-2.9-llama3-8b",
		"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 "dphn/dolphin-2.9-llama3-8b" \
        --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": "dphn/dolphin-2.9-llama3-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use dphn/dolphin-2.9-llama3-8b with Docker Model Runner:
```
docker model run hf.co/dphn/dolphin-2.9-llama3-8b
```

How to access function calling capabilities?

#15

by pyraminded - opened Apr 25, 2024

Discussion

pyraminded

Apr 25, 2024

Thank you for this work!

Model card says dolphin has function calling capabilities. I'm looking for information on how I would provide my functions, their purpose, parameters etc. for the model so that it can prompt me to use them when appropriate.

Charles99

Apr 30, 2024

How to call function call? Is there any example?

esab

Apr 30, 2024

does this model uses the openchatml to access to the function call/tools? how to access to this capabilities using ollama?

g-ronimo

Apr 30, 2024

they trained it on Locutusque/function-calling-chatml
try sth like this:

<|im_start|>system
You are a helpful assistant with access to the following functions. Use them if required -
    {
    "name": "get_exchange_rate",
    "description": "Get the exchange rate between two currencies",
    "parameters": {
        "type": "object",
        "properties": {
            "base_currency": {
                "type": "string",
                "description": "The currency to convert from"
            },
            "target_currency": {
                "type": "string",
                "description": "The currency to convert to"
            }
        },
        "required": [
            "base_currency",
            "target_currency"
        ]
    }
}<|im_end|>
<|im_start|>user
Can you book a flight for me from New York to London?<|im_end|>
<|im_start|>assistant

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