Instructions to use denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa with Transformers:

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

pipe = pipeline("text-generation", model="denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa")
model = AutoModelForCausalLM.from_pretrained("denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa

SGLang

How to use denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa 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 "denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa" \
    --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": "denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa",
		"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 "denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa" \
        --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": "denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa with Docker Model Runner:
```
docker model run hf.co/denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa
```

The Drummer becomes hornier

Recipe based on MarsupialAI/Monstral-123B but uses TheDrummer/Behemoth-123B-v1.1 as the base.

This is a merge of pre-trained language models created using mergekit.

GGUF Quants:

GGUF (static): mradermacher/Behemoth-v1.1-Magnum-v4-123B-GGUF
GGUF (weighted/imatrix): mradermacher/Behemoth-v1.1-Magnum-v4-123B-i1-GGUF

Thank you mradermacher for honoring my request.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: TheDrummer/Behemoth-123B-v1.1
  - model: anthracite-org/magnum-v4-123b
merge_method: slerp
base_model: TheDrummer/Behemoth-123B-v1.1
parameters:
  t: [0.1, 0.3, 0.6, 0.3, 0.1]
dtype: float16

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Model tree for denru/Behemoth-v1.1-Magnum-v4-123B-5_0bpw-h6-exl2-pippa

TheDrummer/Behemoth-123B-v1.1

anthracite-org/magnum-v4-123b

Merge model

this model