Instructions to use Novaciano/Sapo-3.2-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Novaciano/Sapo-3.2-1B with Transformers:

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

pipe = pipeline("text-generation", model="Novaciano/Sapo-3.2-1B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("Novaciano/Sapo-3.2-1B")
model = AutoModelForMultimodalLM.from_pretrained("Novaciano/Sapo-3.2-1B")
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 Novaciano/Sapo-3.2-1B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Novaciano/Sapo-3.2-1B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Novaciano/Sapo-3.2-1B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Novaciano/Sapo-3.2-1B

SGLang

How to use Novaciano/Sapo-3.2-1B 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 "Novaciano/Sapo-3.2-1B" \
    --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": "Novaciano/Sapo-3.2-1B",
		"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 "Novaciano/Sapo-3.2-1B" \
        --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": "Novaciano/Sapo-3.2-1B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Novaciano/Sapo-3.2-1B with Docker Model Runner:
```
docker model run hf.co/Novaciano/Sapo-3.2-1B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Sapo 3.2 1B

Los batracios anuros han sido muy empleados en la iconografía del mal.

Uno de los momentos claves de una "misa negra", era el acto de "partir el sapo", parodia de la eucaristía católica.

El sapo era una de las formas como se aparecían los demonios, por ejemplo, a Santa Teresa.

En el arte, es común ver a batracios como la materialización de espíritus inmundos.

Esto puede tener su origen en la visión de San Juan (Ap. 16,13).

Modelos mezclados

Los siguientes modelos están inclyidos en la mezcla:

Configuración

Configuración YAML usada para producir este modelo:

base_model: xdrshjr/llama3.2_1b_uncensored_5000_8epoch_lora
merge_method: model_stock
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0]
models:
- model: suayptalha/FastLlama-3.2-1B-Instruct
- model: Weyaxi/Einstein-v8-Llama3.2-1B

Downloads last month: 3

Safetensors

Model size

1B params

Tensor type

BF16

Model tree for Novaciano/Sapo-3.2-1B

Weyaxi/Einstein-v8-Llama3.2-1B

suayptalha/FastLlama-3.2-1B-Instruct

xdrshjr/llama3.2_1b_uncensored_5000_8epoch_lora

Merge model

this model

Quantizations

2 models