Instructions to use PygmalionAI/pygmalion-6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PygmalionAI/pygmalion-6b with Transformers:

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

pipe = pipeline("text-generation", model="PygmalionAI/pygmalion-6b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("PygmalionAI/pygmalion-6b")
model = AutoModelForCausalLM.from_pretrained("PygmalionAI/pygmalion-6b")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use PygmalionAI/pygmalion-6b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "PygmalionAI/pygmalion-6b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PygmalionAI/pygmalion-6b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/PygmalionAI/pygmalion-6b

SGLang

How to use PygmalionAI/pygmalion-6b 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 "PygmalionAI/pygmalion-6b" \
    --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": "PygmalionAI/pygmalion-6b",
		"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 "PygmalionAI/pygmalion-6b" \
        --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": "PygmalionAI/pygmalion-6b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use PygmalionAI/pygmalion-6b with Docker Model Runner:
```
docker model run hf.co/PygmalionAI/pygmalion-6b
```

ErisXx commited on Feb 27, 2023

Commit

3b5e68f

1 Parent(s): 2a0d744

Update README.md

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README.md +4 -2

README.md CHANGED Viewed

@@ -2,11 +2,13 @@
 license: creativeml-openrail-m
 language:
 - en
-thumbnail:
 tags:
 - text generation
 - conversational
 inference: false
 ---
 # Pygmalion 6B
@@ -56,4 +58,4 @@ Apart from chat history, you can also just add example conversations in `[DIALOG
 ## Known issues
-We haven't played around with the model enough to enumerate them. Feel free to give us some feedback!

 license: creativeml-openrail-m
 language:
 - en
+thumbnail: null
 tags:
 - text generation
 - conversational
 inference: false
+metrics:
+- character
 ---
 # Pygmalion 6B
 ## Known issues
+We haven't played around with the model enough to enumerate them. Feel free to give us some feedback!