Instructions to use TehVenom/Pygmalion_AlpacaLora-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TehVenom/Pygmalion_AlpacaLora-7b with Transformers:

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

pipe = pipeline("text-generation", model="TehVenom/Pygmalion_AlpacaLora-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TehVenom/Pygmalion_AlpacaLora-7b")
model = AutoModelForCausalLM.from_pretrained("TehVenom/Pygmalion_AlpacaLora-7b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TehVenom/Pygmalion_AlpacaLora-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TehVenom/Pygmalion_AlpacaLora-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TehVenom/Pygmalion_AlpacaLora-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TehVenom/Pygmalion_AlpacaLora-7b

SGLang

How to use TehVenom/Pygmalion_AlpacaLora-7b 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 "TehVenom/Pygmalion_AlpacaLora-7b" \
    --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": "TehVenom/Pygmalion_AlpacaLora-7b",
		"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 "TehVenom/Pygmalion_AlpacaLora-7b" \
        --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": "TehVenom/Pygmalion_AlpacaLora-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TehVenom/Pygmalion_AlpacaLora-7b with Docker Model Runner:
```
docker model run hf.co/TehVenom/Pygmalion_AlpacaLora-7b
```

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Check out the documentation for more information.

The LLaMA based Pygmalion-7b model:

https://huggingface.co/PygmalionAI/pygmalion-7b

Merged alongside Tloen's Alpaca LoRA:

https://huggingface.co/tloen/alpaca-lora-7b

This was done to test whether LoRAs trained for other LLaMA fine tunes worked for Pygmalion, and to have it available on inference backends that do not support LoRAs just yet.

Treat this as a normal HF Transformers model.

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