Instructions to use cgato/Thespis-13b-v0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cgato/Thespis-13b-v0.3 with Transformers:

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

pipe = pipeline("text-generation", model="cgato/Thespis-13b-v0.3")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cgato/Thespis-13b-v0.3")
model = AutoModelForCausalLM.from_pretrained("cgato/Thespis-13b-v0.3", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cgato/Thespis-13b-v0.3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cgato/Thespis-13b-v0.3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cgato/Thespis-13b-v0.3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/cgato/Thespis-13b-v0.3

SGLang

How to use cgato/Thespis-13b-v0.3 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 "cgato/Thespis-13b-v0.3" \
    --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": "cgato/Thespis-13b-v0.3",
		"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 "cgato/Thespis-13b-v0.3" \
        --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": "cgato/Thespis-13b-v0.3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use cgato/Thespis-13b-v0.3 with Docker Model Runner:
```
docker model run hf.co/cgato/Thespis-13b-v0.3
```
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.

Thespis-13b-v0.4

This model is a personal project. It uses a vanilla chat template and is focused on providing multiturn sfw and nsfw RP experience.

This model works best with internet style RP using standard markup with asterisks surrounding actions and no quotes around dialogue.

It uses the following data:

3000 samples from Claude Multiround Chat 30k dataset
6000 samples from Pippa Dataset
3000 samples from Puffin Dataset
3800 samples of hand curated RP conversation with various characters.

Works with standard chat format for Ooba or SillyTavern.

Prompt Format: Chat

{System Prompt}

Username: {Input}
BotName: {Response}
Username: {Input}
BotName: {Response}

Turn Template (for Ooba): You can either bake usernames into the prompt directly for ease of use or programatically add them if running through the API to use as a chatbot.

<|user|>{Username}: <|user-message|>\n<|bot|>{BotName}: <|bot-message|>\n

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Quantizations

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