Instructions to use Lyon28/caca-650M-untrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Lyon28/caca-650M-untrained with Transformers:

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

pipe = pipeline("text-generation", model="Lyon28/caca-650M-untrained", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Lyon28/caca-650M-untrained", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Lyon28/caca-650M-untrained with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Lyon28/caca-650M-untrained"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lyon28/caca-650M-untrained",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Lyon28/caca-650M-untrained

SGLang

How to use Lyon28/caca-650M-untrained 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 "Lyon28/caca-650M-untrained" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lyon28/caca-650M-untrained",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Lyon28/caca-650M-untrained" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lyon28/caca-650M-untrained",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Lyon28/caca-650M-untrained with Docker Model Runner:
```
docker model run hf.co/Lyon28/caca-650M-untrained
```

caca-650M-untrained / config.json

Lyon28

Upload config.json with huggingface_hub

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	{
	"architectures": [
	"CacaForCausalLM"
	],
	"attention_bias": false,
	"attention_dropout": 0.0,
	"attn_logit_softcapping": null,
	"auto_map": {
	"AutoConfig": "configuration_caca.CacaConfig",
	"AutoModel": "modeling_caca.CacaModel",
	"AutoModelForCausalLM": "modeling_caca.CacaForCausalLM"
	},
	"bos_token_id": 2,
	"dtype": "bfloat16",
	"embedding_dropout": 0.0,
	"eos_token_id": 1,
	"final_logit_softcapping": null,
	"gradient_checkpointing": false,
	"head_dim": 128,
	"hidden_activation": "silu",
	"hidden_dropout": 0.0,
	"hidden_size": 1280,
	"initializer_range": 0.02,
	"intermediate_size": 5120,
	"kv_lora_rank": 213,
	"layer_types": [
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention",
	"sliding_attention",
	"full_attention"
	],
	"max_position_embeddings": 8192,
	"model_type": "caca",
	"mtp_loss_weight": 0.3,
	"num_attention_heads": 10,
	"num_hidden_layers": 20,
	"num_key_value_heads": 8,
	"num_mtp_tokens": 1,
	"pad_token_id": 0,
	"q_lora_rank": 426,
	"qk_nope_head_dim": 64,
	"qk_rope_head_dim": 32,
	"query_pre_attn_scalar": 128,
	"rms_norm_eps": 1e-06,
	"rope_parameters": {
	"beta_fast": 32,
	"beta_slow": 1,
	"factor": 4.0,
	"original_max_position_embeddings": 8192,
	"rope_theta": 10000.0,
	"rope_type": "yarn"
	},
	"sliding_window": 4096,
	"tie_word_embeddings": true,
	"transformers_version": "5.13.1",
	"use_cache": true,
	"use_mla": true,
	"use_qk_norm": true,
	"v_head_dim": 128,
	"vocab_size": 32000
	}