Instructions to use AMT-Studio/StellarAI-1-beta-0.05b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AMT-Studio/StellarAI-1-beta-0.05b with Transformers:

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

pipe = pipeline("text-generation", model="AMT-Studio/StellarAI-1-beta-0.05b", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("AMT-Studio/StellarAI-1-beta-0.05b", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AMT-Studio/StellarAI-1-beta-0.05b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AMT-Studio/StellarAI-1-beta-0.05b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AMT-Studio/StellarAI-1-beta-0.05b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/AMT-Studio/StellarAI-1-beta-0.05b

SGLang

How to use AMT-Studio/StellarAI-1-beta-0.05b 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 "AMT-Studio/StellarAI-1-beta-0.05b" \
    --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": "AMT-Studio/StellarAI-1-beta-0.05b",
		"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 "AMT-Studio/StellarAI-1-beta-0.05b" \
        --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": "AMT-Studio/StellarAI-1-beta-0.05b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AMT-Studio/StellarAI-1-beta-0.05b with Docker Model Runner:
```
docker model run hf.co/AMT-Studio/StellarAI-1-beta-0.05b
```

StellarAI-1-beta-0.05b / tokenizer_config.json

AMT-Studio

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	{
	"name_or_path": "stellarai-tiny",
	"do_lower_case": false,
	"model_max_length": 1024,
	"padding_side": "right",
	"truncation_side": "right",
	"bos_token": "[BOS]",
	"eos_token": "[EOS]",
	"unk_token": "[UNK]",
	"sep_token": "[SEP]",
	"pad_token": "[PAD]",
	"cls_token": "[CLS]",
	"mask_token": "[MASK]",
	"additional_special_tokens": ["[IMG]", "[BOI]", "[EOI]"],
	"strip_accents": false,
	"clean_up_tokenization_spaces": true,
	"comment_tokens": [],
	"added_tokens_decoder": {
	"0": {"content": "[PAD]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"1": {"content": "[BOS]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"2": {"content": "[EOS]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"3": {"content": "[UNK]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"4": {"content": "[MASK]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"5": {"content": "[CLS]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"6": {"content": "[SEP]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"7": {"content": "[IMG]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"8": {"content": "[BOI]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true},
	"9": {"content": "[EOI]", "lstrip": false, "normalized": false, "rstrip": false, "single_word": false, "special": true}
	}
	}