Instructions to use cgato/L3-TheSpice-8b-v0.8.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cgato/L3-TheSpice-8b-v0.8.3 with Transformers:

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

pipe = pipeline("text-generation", model="cgato/L3-TheSpice-8b-v0.8.3")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cgato/L3-TheSpice-8b-v0.8.3")
model = AutoModelForCausalLM.from_pretrained("cgato/L3-TheSpice-8b-v0.8.3")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use cgato/L3-TheSpice-8b-v0.8.3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cgato/L3-TheSpice-8b-v0.8.3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cgato/L3-TheSpice-8b-v0.8.3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/cgato/L3-TheSpice-8b-v0.8.3

SGLang

How to use cgato/L3-TheSpice-8b-v0.8.3 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/L3-TheSpice-8b-v0.8.3" \
    --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/L3-TheSpice-8b-v0.8.3",
		"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/L3-TheSpice-8b-v0.8.3" \
        --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/L3-TheSpice-8b-v0.8.3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use cgato/L3-TheSpice-8b-v0.8.3 with Docker Model Runner:
```
docker model run hf.co/cgato/L3-TheSpice-8b-v0.8.3
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Now not overtrained and with the tokenizer fix to base llama3. Trained for 3 epochs.

The latest TheSpice, dipped in Mama Liz's LimaRP Oil. I've focused on making the model more flexible and provide a more unique experience. I'm still working on cleaning up my dataset, but I've shrunken it down a lot to focus on a "less is more" approach. This is ultimate a return to form of the way I used to train Thespis, with more of a focus on a small hand edited dataset.

Datasets Used

Capybara
Claude Multiround 30k
Augmental
ToxicQA
Yahoo Answers
Airoboros 3.1
LimaRP

Features ( Examples from 0.1.1 because I'm too lazy to take new screenshots. Its tested tho. )

Narration

If you request information on objects or characters in the scene, the model will narrate it to you. Most of the time, without moving the story forward.

You can look at anything mostly as long as you end it with "What do I see?"

You can also request to know what a character is thinking or planning.

You can ask for a quick summary on the character as well.

Before continuing the conversation as normal.

Prompt Format: Chat ( The default Ooba template and Silly Tavern Template )

If you're using Ooba in verbose mode as a server, you can check if you're console is logging something that looks like this.

{System Prompt}

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

Presets

All screenshots above were taken with the below SillyTavern Preset.

Recommended Silly Tavern Preset -> (Temp: 1.25, MinP: 0.1, RepPen: 1.05)

This is a roughly equivalent Kobold Horde Preset.

Recommended Kobold Horde Preset -> MinP

Disclaimer

Please prompt responsibly and take anything outputted by any Language Model with a huge grain of salt. Thanks!

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Safetensors

Model size

8B params

Tensor type

BF16

Model tree for cgato/L3-TheSpice-8b-v0.8.3

Merges

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Quantizations

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L3-TheSpice-8b-v0.8.3