Instructions to use dphn/dolphin-2.9.2-qwen2-72b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dphn/dolphin-2.9.2-qwen2-72b with Transformers:

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

pipe = pipeline("text-generation", model="dphn/dolphin-2.9.2-qwen2-72b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("dphn/dolphin-2.9.2-qwen2-72b")
model = AutoModelForCausalLM.from_pretrained("dphn/dolphin-2.9.2-qwen2-72b", 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-2.9.2-qwen2-72b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dphn/dolphin-2.9.2-qwen2-72b"
# 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-2.9.2-qwen2-72b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/dphn/dolphin-2.9.2-qwen2-72b

SGLang

How to use dphn/dolphin-2.9.2-qwen2-72b 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-2.9.2-qwen2-72b" \
    --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-2.9.2-qwen2-72b",
		"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-2.9.2-qwen2-72b" \
        --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-2.9.2-qwen2-72b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use dphn/dolphin-2.9.2-qwen2-72b with Docker Model Runner:
```
docker model run hf.co/dphn/dolphin-2.9.2-qwen2-72b
```

Token Configuration Correction

by bigstorm - opened Jun 17, 2024

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

-1

bigstorm

Jun 17, 2024

•

edited Jun 17, 2024

Good afternoon!

When deploying the this model locally, I discovered what I believe to be a bug in the configuration of tokenizer_config.json and config.json.

tokenizer_config.json: The "bos_token" is set to null when I believe it should be set to "<|im_start|>".

config.json: The "bos_token_id" is not set, but I believe it should be set to 151643 for the token "<|im_start|>".

I've included the proposed changes in this issue. This issue also affects cognitivecomputations/dolphin-2.9.2-qwen2-7b. I'll submit another PR there if we are in agreement here.

Thank you for you contributions; I love these finetunes.

Warm regards,
Ben

Token Config Fixes361a3abd

Revert generation_config changesdb67dc28

bigstorm changed pull request status to open Jun 17, 2024

Crystalcareai

Jun 17, 2024

cognitive contributions. Thanks for the PR - I added special tokens when training the model when I didn't need to. Old habits die hard.

Crystalcareai changed pull request status to merged Jun 17, 2024

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