Instructions to use Lazycuber/Janemalion-6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Lazycuber/Janemalion-6B with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Lazycuber/Janemalion-6B")
model = AutoModelForCausalLM.from_pretrained("Lazycuber/Janemalion-6B")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Lazycuber/Janemalion-6B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Lazycuber/Janemalion-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": "Lazycuber/Janemalion-6B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Lazycuber/Janemalion-6B

SGLang

How to use Lazycuber/Janemalion-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 "Lazycuber/Janemalion-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": "Lazycuber/Janemalion-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 "Lazycuber/Janemalion-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": "Lazycuber/Janemalion-6B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Lazycuber/Janemalion-6B with Docker Model Runner:
```
docker model run hf.co/Lazycuber/Janemalion-6B
```

Update README.md

by Lazycuber - opened Jun 21, 2023

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-1

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README.md +3 -1

README.md CHANGED Viewed

@@ -7,4 +7,6 @@ pipeline_tag: text-generation
 A model Merged using Pyg P8V2 (60%) + GPT-J-6B-Janeway (40%)
 Focuses on SFW and NSFW roleplay.
-Works better using the pygmalion formatting.

 A model Merged using Pyg P8V2 (60%) + GPT-J-6B-Janeway (40%)
 Focuses on SFW and NSFW roleplay.
+Works better using the pygmalion formatting.
+Reupload version of [Rencox/PygJane6B](https://huggingface.co/Rencox/PygJane6B)