Not-For-All-Audiences

Instructions to use Khetterman/AbominationScience-12B-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Khetterman/AbominationScience-12B-v4 with Transformers:

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

pipe = pipeline("text-generation", model="Khetterman/AbominationScience-12B-v4")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Khetterman/AbominationScience-12B-v4")
model = AutoModelForCausalLM.from_pretrained("Khetterman/AbominationScience-12B-v4", 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 Khetterman/AbominationScience-12B-v4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Khetterman/AbominationScience-12B-v4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Khetterman/AbominationScience-12B-v4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Khetterman/AbominationScience-12B-v4

SGLang

How to use Khetterman/AbominationScience-12B-v4 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 "Khetterman/AbominationScience-12B-v4" \
    --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": "Khetterman/AbominationScience-12B-v4",
		"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 "Khetterman/AbominationScience-12B-v4" \
        --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": "Khetterman/AbominationScience-12B-v4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Khetterman/AbominationScience-12B-v4 with Docker Model Runner:
```
docker model run hf.co/Khetterman/AbominationScience-12B-v4
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

AbominationScience-12B-v4

When the choice is not random.

This is an interesting merge of 11 cool models, created using mergekit. Enjoy exploring :)

Merge Details

Method

This model was merged using the multistep process and remerge with some model variations for best result.

Models

The following models were included in the merge:

Configuration

The following YAML configurations was used to produce this model:

# AbominationScience
# It's a good model, I used it as a base for this merge.
models:
  - model: Trappu/Abomination-merge-attempt-12B
  - model: benhaotang/nemo-math-science-philosophy-12B
merge_method: slerp
base_model: Trappu/Abomination-merge-attempt-12B
dtype: bfloat16
parameters:
  t: [0.8, 0.2, 0.8, 0.2, 0.8, 0.2, 0.8]

# SCUMCL
models:
  - model: VongolaChouko/Starcannon-Unleashed-12B-v1.0
  - model: FallenMerick/MN-Chunky-Lotus-12B
merge_method: slerp
base_model: VongolaChouko/Starcannon-Unleashed-12B-v1.0
dtype: bfloat16
parameters:
  t: [0.7, 0.3, 0.7, 0.3, 0.7, 0.3, 0.7]

# SISMMU
models:
  - model: Nohobby/MN-12B-Siskin-v0.2
  - model: ThijsL202/MadMix-Unleashed-12B
merge_method: slerp
base_model: Nohobby/MN-12B-Siskin-v0.2
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0]

# PLECAD
models:
  - model: GalrionSoftworks/Pleiades-12B-v1
  - model: GalrionSoftworks/Canidori-12B-v1
merge_method: slerp
base_model: GalrionSoftworks/Pleiades-12B-v1
dtype: bfloat16
parameters:
  t: [0.7, 0.3, 0.7, 0.3, 0.7, 0.3, 0.7]

# Positive-12B-v1 and Negative-12B-v1 are the basis of diversity for the base model.
# I've lost the exact config, but it was most likely a slerp like the one in SCUMCL/SISMMU/PLECAD.
# Positive-12B-v1 = SCUMCL + SISMMU.
# Negative-12B-v1 = PLECAD + AbominationScience.

# AbominationScience-12B-v2
models:
  - model: F:/Positive-12B-v1
    parameters:
      density: [0.5, 0.4, 0.6, 0.3, 0.7, 0.2, 0.8, 0.1, 0.9,  0.1, 0.9, 0.1, 0.9,  0.1, 0.9, 0.2, 0.8, 0.3, 0.7, 0.4, 0.6, 0.5]
      weight:  [0.5, 0.6, 0.4, 0.7, 0.3, 0.8, 0.2, 0.9, 0.1,  0.9, 0.1, 0.9, 0.1,  0.9, 0.1, 0.8, 0.2, 0.7, 0.3, 0.6, 0.4, 0.5]
  - model: F:/Negative-12B-v1
    parameters:
      density: [0.5, 0.6, 0.4, 0.7, 0.3, 0.8, 0.2, 0.9, 0.1,  0.9, 0.1, 0.9, 0.1,  0.9, 0.1, 0.8, 0.2, 0.7, 0.3, 0.6, 0.4, 0.5]
      weight:  [0.5, 0.4, 0.6, 0.3, 0.7, 0.2, 0.8, 0.1, 0.9,  0.1, 0.9, 0.1, 0.9,  0.1, 0.9, 0.2, 0.8, 0.3, 0.7, 0.4, 0.6, 0.5]
merge_method: dare_ties
base_model: F:/AbominationScience
dtype: bfloat16

# AbominationScience-12B-v3
# Della merge with a good base to form an interesting core
models:
  - model: F:/AbominationScience
    parameters:
      weight:  [0.5, 0.6, 0.4, 0.7, 0.3, 0.8, 0.2, 0.8, 0.2, 0.7, 0.3, 0.6, 0.4, 0.5]
      density: [0.5, 0.4, 0.6, 0.3, 0.7, 0.2, 0.8, 0.2, 0.8, 0.3, 0.7, 0.4, 0.6, 0.5]
merge_method: della
parameters:
  epsilon: 0.123456789
  lambda:  0.987654321
base_model: F:/AbominationScience-12B-v2
dtype: bfloat16

# AbominationScience-12B-v4
# Final shift the model to three very good bases.
models:
  - model: inflatebot/MN-12B-Mag-Mell-R1
  - model: FallenMerick/MN-Violet-Lotus-12B
  - model: Azazelle/MN-Halide-12b-v1.0
merge_method: model_stock
base_model: F:/AbominationScience-12B-v3
dtype: bfloat16