Instructions to use Naphula/Smilodon-9B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Naphula/Smilodon-9B-v1 with Transformers:

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

pipe = pipeline("text-generation", model="Naphula/Smilodon-9B-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Naphula/Smilodon-9B-v1")
model = AutoModelForCausalLM.from_pretrained("Naphula/Smilodon-9B-v1")
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

vLLM

How to use Naphula/Smilodon-9B-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Naphula/Smilodon-9B-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Naphula/Smilodon-9B-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Naphula/Smilodon-9B-v1

SGLang

How to use Naphula/Smilodon-9B-v1 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 "Naphula/Smilodon-9B-v1" \
    --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": "Naphula/Smilodon-9B-v1",
		"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 "Naphula/Smilodon-9B-v1" \
        --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": "Naphula/Smilodon-9B-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Naphula/Smilodon-9B-v1 with Docker Model Runner:
```
docker model run hf.co/Naphula/Smilodon-9B-v1
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Smilodon 9B v1

The successor to Smilodon v0.5 [v0k]. This edition does not aim to be uncensored (although jailbreaks work), but more creative. Further ablation techniques are under study for future versions.

v1 yaml

architecture: MistralForCausalLM
merge_method: karcher
dtype: bfloat16
models:
  - model: allura-org/G2-9B-Sugarquill-v0
  - model: anthracite-org/magnum-v4-9b
  - model: crestf411/gemma2-9B-sunfall-v0.5.2
  - model: ehristoforu/Gemma2-9B-it-psy10k-mental_health
  - model: Hastagaras/Gemmoy-9B-G2-MK.3
  - model: lemon07r/Gemma-2-Ataraxy-v4d-9B
  - model: nbeerbower/Gemma2-Gutenberg-Doppel-9B
  - model: sam-paech/Delirium-v1
  - model: sam-paech/Quill-v1
  - model: TheDrummer/Tiger-Gemma-9B-v1
  - model: TheDrummer/Tiger-Gemma-9B-v2
  - model: TheDrummer/Tiger-Gemma-9B-v3
parameters:
tokenizer:
source: union
chat_template: auto

v0.5 yaml

base_model: TheDrummer/Tiger-Gemma-9B-v3
merge_method: dare_ties
architecture: Gemma2ForCausalLM
dtype: bfloat16
models:
  - model: allura-org/G2-9B-Sugarquill-v0
    parameters:
      density: 0.4
      weight: 0.05
  - model: anthracite-org/magnum-v4-9b
    parameters:
      density: 0.4
      weight: 0.05
  - model: crestf411/gemma2-9B-sunfall-v0.5.2
    parameters:
      density: 0.4
      weight: 0.05
  - model: Hastagaras/Gemmoy-9B-G2-MK.3
    parameters:
      density: 0.4
      weight: 0.05
  - model: nbeerbower/Gemma2-Gutenberg-Doppel-9B
    parameters:
      density: 0.4
      weight: 0.05
  - model: sam-paech/Delirium-v1
    parameters:
      density: 0.5
      weight: 0.075
  - model: sam-paech/Quill-v1
    parameters:
      density: 0.5
      weight: 0.075
  - model: TheDrummer/Tiger-Gemma-9B-v3
    parameters:
      density: 0.7
      weight: 0.6
tokenizer:
source: union
chat_template: auto