Instructions to use Aeala/VicUnlocked-alpaca-30b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Aeala/VicUnlocked-alpaca-30b with Transformers:

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

pipe = pipeline("text-generation", model="Aeala/VicUnlocked-alpaca-30b")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Aeala/VicUnlocked-alpaca-30b")
model = AutoModelForCausalLM.from_pretrained("Aeala/VicUnlocked-alpaca-30b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Aeala/VicUnlocked-alpaca-30b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Aeala/VicUnlocked-alpaca-30b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Aeala/VicUnlocked-alpaca-30b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Aeala/VicUnlocked-alpaca-30b

SGLang

How to use Aeala/VicUnlocked-alpaca-30b 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 "Aeala/VicUnlocked-alpaca-30b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Aeala/VicUnlocked-alpaca-30b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Aeala/VicUnlocked-alpaca-30b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Aeala/VicUnlocked-alpaca-30b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Aeala/VicUnlocked-alpaca-30b with Docker Model Runner:
```
docker model run hf.co/Aeala/VicUnlocked-alpaca-30b
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

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Check out the documentation for more information.

Model Info

Merge of my VicUnlocked-alpaca-half-30b LoRA

Important Note: While this is trained on a cleaned ShareGPT dataset like Vicuna used, this was trained in the Alpaca format, so prompting should be something like:

### Instruction:

<prompt> (without the <>)

### Response:

Benchmarks

wikitext2: 4.372413635253906 ptb-new: 24.69171714782715 c4-new: 6.469308853149414

Results generated with GPTQ evals (not quantized) thanks to Neko-Institute-of-Science

Downloads last month: 69

Safetensors

Model size

33B params

Tensor type

F32

F16

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Quantizations

4 models

Aeala
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VicUnlocked-alpaca-30b

Model Info

Benchmarks

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