Instructions to use AstraMindAI/AstraQuasar-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AstraMindAI/AstraQuasar-4B with Transformers:

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

pipe = pipeline("text-generation", model="AstraMindAI/AstraQuasar-4B", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AstraMindAI/AstraQuasar-4B", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("AstraMindAI/AstraQuasar-4B", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use AstraMindAI/AstraQuasar-4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AstraMindAI/AstraQuasar-4B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AstraMindAI/AstraQuasar-4B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/AstraMindAI/AstraQuasar-4B

SGLang

How to use AstraMindAI/AstraQuasar-4B 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 "AstraMindAI/AstraQuasar-4B" \
    --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": "AstraMindAI/AstraQuasar-4B",
		"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 "AstraMindAI/AstraQuasar-4B" \
        --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": "AstraMindAI/AstraQuasar-4B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AstraMindAI/AstraQuasar-4B with Docker Model Runner:
```
docker model run hf.co/AstraMindAI/AstraQuasar-4B
```

AstraQuasar-4B / config.json

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Update config.json

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	{
	"_name_or_path": "AstraMindAI/AstraQuasar-4B",
	"architectures": [
	"QuasarForCausalLM"
	],
	"attention_dropout": 0.0,
	"auto_map": {
	"AutoConfig": "AstraMindAI/AstraQuasar-4B--configuration_quasar.QuasarConfig",
	"AutoModelForCausalLM": "AstraMindAI/AstraQuasar-4B--modeling_quasar.QuasarForCausalLM"
	},
	"bos_token_id": 50256,
	"embd_pdrop": 0.0,
	"eos_token_id": 50256,
	"gated_activation": false,
	"remove_ff_bias": true,
	"simple_norm": false,
	"hidden_act": "gelu_new",
	"hidden_size": 2560,
	"initializer_range": 0.02,
	"intermediate_size": 10240,
	"layer_norm_eps": 1e-05,
	"max_position_embeddings": 32768,
	"model_type": "phi",
	"num_attention_heads": 32,
	"num_hidden_layers": 57,
	"num_key_value_heads": 32,
	"partial_rotary_factor": 0.4,
	"qk_layernorm": false,
	"resid_pdrop": 0.1,
	"rope_scaling": null,
	"rope_theta": 10000.0,
	"tie_word_embeddings": false,
	"torch_dtype": "float16",
	"transformers_version": "4.38.0.dev0",
	"use_cache": true,
	"vocab_size": 51200,
	"duplicate_trick": true,
	"duplicate_grad": true,
	"layer_ranges": [[0, 16],[8, 24],[17, 32],[25, 40],[33, 49],[40, 56]],
	"sliding_window": 2048
	}