Text Generation
Transformers
Safetensors
qwen3
feature-extraction
speculative-decoding
dspark
dflash
specforge
sglang
custom_code
text-generation-inference
Instructions to use RadixArk/Inkling-Small-DSpark-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RadixArk/Inkling-Small-DSpark-Preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="RadixArk/Inkling-Small-DSpark-Preview", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("RadixArk/Inkling-Small-DSpark-Preview", trust_remote_code=True) model = AutoModel.from_pretrained("RadixArk/Inkling-Small-DSpark-Preview", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use RadixArk/Inkling-Small-DSpark-Preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RadixArk/Inkling-Small-DSpark-Preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RadixArk/Inkling-Small-DSpark-Preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/RadixArk/Inkling-Small-DSpark-Preview
- SGLang
How to use RadixArk/Inkling-Small-DSpark-Preview 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 "RadixArk/Inkling-Small-DSpark-Preview" \ --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": "RadixArk/Inkling-Small-DSpark-Preview", "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 "RadixArk/Inkling-Small-DSpark-Preview" \ --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": "RadixArk/Inkling-Small-DSpark-Preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use RadixArk/Inkling-Small-DSpark-Preview with Docker Model Runner:
docker model run hf.co/RadixArk/Inkling-Small-DSpark-Preview
| { | |
| "architectures": [ | |
| "DSparkDraftModel" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoModel": "dspark.DSparkDraftModel" | |
| }, | |
| "block_size": 15, | |
| "bos_token_id": null, | |
| "confidence_head_with_markov": true, | |
| "dflash_config": { | |
| "mask_token_id": 200064, | |
| "target_layer_ids": [ | |
| 5, | |
| 11, | |
| 23, | |
| 29, | |
| 35 | |
| ] | |
| }, | |
| "dtype": "bfloat16", | |
| "enable_confidence_head": true, | |
| "eos_token_id": [ | |
| 200006, | |
| 200000, | |
| 200002, | |
| 200003 | |
| ], | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8192, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "markov_head_type": "vanilla", | |
| "markov_rank": 256, | |
| "max_position_embeddings": 1048576, | |
| "max_window_layers": 5, | |
| "model_type": "qwen3", | |
| "num_attention_heads": 64, | |
| "num_hidden_layers": 5, | |
| "num_key_value_heads": 16, | |
| "num_target_layers": 42, | |
| "pad_token_id": 200006, | |
| "rms_norm_eps": 1e-05, | |
| "rope_parameters": { | |
| "beta_fast": 32.0, | |
| "beta_slow": 1.0, | |
| "factor": 128.0, | |
| "original_max_position_embeddings": 8192, | |
| "rope_theta": 8000000, | |
| "rope_type": "yarn" | |
| }, | |
| "rope_scaling": { | |
| "beta_fast": 32.0, | |
| "beta_slow": 1.0, | |
| "factor": 128.0, | |
| "original_max_position_embeddings": 8192, | |
| "rope_type": "yarn" | |
| }, | |
| "rope_theta": 8000000, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "5.12.1", | |
| "use_cache": true, | |
| "use_sliding_window": false, | |
| "vocab_size": 201024 | |
| } |