Instructions to use TehVenom/Pygmalion-Vicuna-1.1-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TehVenom/Pygmalion-Vicuna-1.1-7b with Transformers:

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

pipe = pipeline("text-generation", model="TehVenom/Pygmalion-Vicuna-1.1-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TehVenom/Pygmalion-Vicuna-1.1-7b")
model = AutoModelForCausalLM.from_pretrained("TehVenom/Pygmalion-Vicuna-1.1-7b")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TehVenom/Pygmalion-Vicuna-1.1-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TehVenom/Pygmalion-Vicuna-1.1-7b"
# 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-Vicuna-1.1-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TehVenom/Pygmalion-Vicuna-1.1-7b

SGLang

How to use TehVenom/Pygmalion-Vicuna-1.1-7b 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-Vicuna-1.1-7b" \
    --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-Vicuna-1.1-7b",
		"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-Vicuna-1.1-7b" \
        --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-Vicuna-1.1-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TehVenom/Pygmalion-Vicuna-1.1-7b with Docker Model Runner:
```
docker model run hf.co/TehVenom/Pygmalion-Vicuna-1.1-7b
```
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.

The LLaMA based Pygmalion-7b model:

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

Merged alongside lmsys's Vicuna v1.1 deltas:

https://huggingface.co/lmsys/vicuna-13b-delta-v1.1

This merge was done using an weighted average merge strategy, and the end result is a model composed of:

Pygmalion-7b [60%] + LLaMA Vicuna v1.1 [40%]

This was done under request, but the end result is intended to lean heavily towards Pygmalion's chatting + RP tendencies, and to inherit some of Vicuna's Assistant / Instruct / Helpful properties.

Due to the influence of Pygmalion, this model will very likely generate content that is considered NSFW.

The specific prompting is unknown, but try Pygmalion's prompt styles first, then a mix of the two to see what brings most interesting results.

Treat this as a normal HF Transformers model.

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Safetensors

Model size

7B params

Tensor type

F16

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Quantizations

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