Instructions to use huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated with Transformers:

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

pipe = pipeline("text-generation", model="huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated")
model = AutoModelForCausalLM.from_pretrained("huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated", 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 huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated

SGLang

How to use huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated 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 "huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated" \
    --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": "huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated",
		"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 "huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated" \
        --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": "huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated with Docker Model Runner:
```
docker model run hf.co/huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated
```

Question

by VicoIlFicoFigo - opened Jan 8, 2025

Discussion

VicoIlFicoFigo

Jan 8, 2025

What's the difference between this and dolphin? aren't they both supposed to be uncensored?

huihui-ai

Owner Jan 8, 2025

Some questions are still being left unanswered.

erichartford

Jan 9, 2025

This will be even more uncensored than Dolphin is.
Dolphin has bias that's baked into the base model.
Let's say that, abliteration will not lobotomize Dolphin as hard as it will lobotomize Llama.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment