Instructions to use Monero/WizardLM-13b-OpenAssistant-Uncensored with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Monero/WizardLM-13b-OpenAssistant-Uncensored with Transformers:

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

pipe = pipeline("text-generation", model="Monero/WizardLM-13b-OpenAssistant-Uncensored")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Monero/WizardLM-13b-OpenAssistant-Uncensored")
model = AutoModelForCausalLM.from_pretrained("Monero/WizardLM-13b-OpenAssistant-Uncensored", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Monero/WizardLM-13b-OpenAssistant-Uncensored with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Monero/WizardLM-13b-OpenAssistant-Uncensored"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Monero/WizardLM-13b-OpenAssistant-Uncensored",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Monero/WizardLM-13b-OpenAssistant-Uncensored

SGLang

How to use Monero/WizardLM-13b-OpenAssistant-Uncensored 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 "Monero/WizardLM-13b-OpenAssistant-Uncensored" \
    --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": "Monero/WizardLM-13b-OpenAssistant-Uncensored",
		"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 "Monero/WizardLM-13b-OpenAssistant-Uncensored" \
        --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": "Monero/WizardLM-13b-OpenAssistant-Uncensored",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Monero/WizardLM-13b-OpenAssistant-Uncensored with Docker Model Runner:
```
docker model run hf.co/Monero/WizardLM-13b-OpenAssistant-Uncensored
```

Monero commited on May 27, 2023

Commit

ff8e15f

1 Parent(s): 28072f6

Update README.md

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@@ -16,6 +16,10 @@ This is a Lora merge of Open Assistant 13b - 4 Epoch  with WizardLM-13b Uncensor
 https://huggingface.co/serpdotai/llama-oasst-lora-13B <br>
 https://huggingface.co/ehartford/WizardLM-13B-Uncensored
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 	<style>

 https://huggingface.co/serpdotai/llama-oasst-lora-13B <br>
 https://huggingface.co/ehartford/WizardLM-13B-Uncensored
+## Uncensored
+Use ```### Certainly!``` at the end of your prompt to get answers to anything
 <html>
 <head>
 	<style>