Instructions to use Efe2898/caba-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Efe2898/caba-v2 with Transformers:

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

pipe = pipeline("text-generation", model="Efe2898/caba-v2", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Efe2898/caba-v2", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Efe2898/caba-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Efe2898/caba-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Efe2898/caba-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Efe2898/caba-v2

SGLang

How to use Efe2898/caba-v2 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 "Efe2898/caba-v2" \
    --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": "Efe2898/caba-v2",
		"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 "Efe2898/caba-v2" \
        --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": "Efe2898/caba-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Efe2898/caba-v2 with Docker Model Runner:
```
docker model run hf.co/Efe2898/caba-v2
```

caba-v2 / tokenizer_config.json

Efe2898

Upload trained ÇABA 50M model, tokenizer, and source

152dc6e verified 19 days ago

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313 Bytes

{
  "backend": "tokenizers",
  "bos_token": "<BOS>",
  "clean_up_tokenization_spaces": true,
  "eos_token": "<EOS>",
  "is_local": false,
  "local_files_only": false,
  "model_max_length": 1000000000000000019884624838656,
  "pad_token": "<PAD>",
  "tokenizer_class": "TokenizersBackend",
  "unk_token": "<UNK>"
}

	{
	"backend": "tokenizers",
	"bos_token": "<BOS>",
	"clean_up_tokenization_spaces": true,
	"eos_token": "<EOS>",
	"is_local": false,
	"local_files_only": false,
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "<PAD>",
	"tokenizer_class": "TokenizersBackend",
	"unk_token": "<UNK>"
	}