Instructions to use maicomputer/alpaca-native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use maicomputer/alpaca-native with Transformers:

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

pipe = pipeline("text-generation", model="maicomputer/alpaca-native")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("maicomputer/alpaca-native")
model = AutoModelForCausalLM.from_pretrained("maicomputer/alpaca-native")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use maicomputer/alpaca-native with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/maicomputer/alpaca-native

SGLang

How to use maicomputer/alpaca-native 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 "maicomputer/alpaca-native" \
    --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": "maicomputer/alpaca-native",
		"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 "maicomputer/alpaca-native" \
        --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": "maicomputer/alpaca-native",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use maicomputer/alpaca-native with Docker Model Runner:
```
docker model run hf.co/maicomputer/alpaca-native
```

Quality seems to be different from the official demo

by kz919 - opened Mar 18, 2023

Discussion

kz919

Mar 18, 2023

Thanks for the great work!!! I have been looking for some pretrained weights since I do not have the compute to do so.
When inputing the same prompt, it's giving some very different results especially in code generation. The official demo seems to be able to generate good executable code to simple leetcode problems, but this one fails to do so. Is it because of the model size difference?

kz919

Mar 18, 2023

Never mind you need the instruction template to make it work, but the weird thing is all the generation ends up with , which is super weird.

mikeliu

Apr 2, 2023

same issure

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