Instructions to use loremipsum3658/dolphin-2.2-indrema-frozen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use loremipsum3658/dolphin-2.2-indrema-frozen with Transformers:

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

pipe = pipeline("text-generation", model="loremipsum3658/dolphin-2.2-indrema-frozen")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("loremipsum3658/dolphin-2.2-indrema-frozen")
model = AutoModelForCausalLM.from_pretrained("loremipsum3658/dolphin-2.2-indrema-frozen", 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 loremipsum3658/dolphin-2.2-indrema-frozen with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "loremipsum3658/dolphin-2.2-indrema-frozen"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "loremipsum3658/dolphin-2.2-indrema-frozen",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/loremipsum3658/dolphin-2.2-indrema-frozen

SGLang

How to use loremipsum3658/dolphin-2.2-indrema-frozen 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 "loremipsum3658/dolphin-2.2-indrema-frozen" \
    --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": "loremipsum3658/dolphin-2.2-indrema-frozen",
		"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 "loremipsum3658/dolphin-2.2-indrema-frozen" \
        --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": "loremipsum3658/dolphin-2.2-indrema-frozen",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use loremipsum3658/dolphin-2.2-indrema-frozen with Docker Model Runner:
```
docker model run hf.co/loremipsum3658/dolphin-2.2-indrema-frozen
```

Dolphin 2.0 🐬 https://erichartford.com/dolphin

Dolphin-2.0-mistral-7b's training was sponsored by a16z.

This model is based on mistralAI, so it is suitable for commercial or non-commercial use.

This model is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant to any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.

Dataset

This dataset is Dolphin, an open-source implementation of Microsoft's Orca

I modified the dataset for uncensoring, deduping, cleaning, and quality.

I added Jon Durbin's excellent Airoboros dataset to increase creativity.

Training

It took 48 hours to train 10 epochs on 4x A100s.

Prompt format: This model (and all my future releases) use ChatML prompt format.

<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>

Example:

<|im_start|>system
you are an expert dolphin trainer<|im_end|>
<|im_start|>user
What is the best way to train a dolphin to obey me?  Please answer step by step.<|im_end|>

Gratitude

This model was made possible by the generous sponsorship of a16z.
Thank you to Microsoft for authoring the Orca paper and inspiring this work.
Special thanks to WingLian, and TheBloke for helpful advice
Thank you to all the other people in the Open Source AI community who have taught me and helped me along the way.

Example Output

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Dataset

Training

Gratitude

Example Output

Datasets used to train loremipsum3658/dolphin-2.2-indrema-frozen