Instructions to use allura-org/Bigger-Body-12b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use allura-org/Bigger-Body-12b with Transformers:

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

pipe = pipeline("text-generation", model="allura-org/Bigger-Body-12b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("allura-org/Bigger-Body-12b")
model = AutoModelForCausalLM.from_pretrained("allura-org/Bigger-Body-12b", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use allura-org/Bigger-Body-12b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "allura-org/Bigger-Body-12b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "allura-org/Bigger-Body-12b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/allura-org/Bigger-Body-12b

SGLang

How to use allura-org/Bigger-Body-12b 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 "allura-org/Bigger-Body-12b" \
    --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": "allura-org/Bigger-Body-12b",
		"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 "allura-org/Bigger-Body-12b" \
        --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": "allura-org/Bigger-Body-12b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use allura-org/Bigger-Body-12b with Docker Model Runner:
```
docker model run hf.co/allura-org/Bigger-Body-12b
```

Bigger-Body-12b / non-lore-README.md

Fizzarolli

Update non-lore-README.md

b353e7a verified over 1 year ago

preview code

Raw

History Blame Contribute Delete

3.23 kB

Bigger Body 12b

A roleplay-focused pseudo full-finetune of Mistral Nemo Instruct. The successor to the Ink series.

Testimonials

First impressions (temp 1, min-p .05-.1)

It passes my silly logic tests (read: me trolling random characters)

Haven't seen any slop yet

Writes short and snappy replies

...yet not too short, like Mahou, and can write longer responses if the context warrants it

Follows card formatting instructions

If this holds up to 16K it will be constantly in the hopper alongside Mag-Mell for me. I'm biased towards shorter responses with smarts. :)

- Tofumagate

tantalizing writing, leagues better then whatever is available online

- Bowza

Fun to use, nice swipe variation, gives me lots to RP off of. Rarely, it'll start to loop, but a quick swipe fixes no problem.

- AliCat

Dataset

The Bigger Body (referred to as Ink v2.1, because that's still the internal name) mix is absolutely disgusting. It's even more cursed than the original Ink mix.

(Public) Original Datasets

Quants

TODO!

Recommended Settings

Chat template: Mistral v7-tekken (NOT v3-tekken !!!! the main difference is that v7 has specific [SYSTEM_PROMPT] and [/SYSTEM_PROMPT] tags)
Recommended samplers (not the be-all-end-all, try some on your own!):

Temp 1.25 / MinP 0.1

Hyperparams

General

Epochs = 2
LR = 1e-5
LR Scheduler = Cosine
Optimizer = Apollo-mini
Optimizer target modules = all_linear
Effective batch size = 16
Weight Decay = 0.01
Warmup steps = 50
Total steps = 920

Credits

Humongous thanks to the people who created the data. I would credit you all, but that would be cheating ;)
Big thanks to all Allura members for testing and emotional support ilya /platonic