Text Generation
Transformers
Safetensors
qwen3
speculative-decoding
dspark
dflash
specforge
sglang
text-generation-inference
Instructions to use inclusionAI/Ling-3.0-flash-dspark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/Ling-3.0-flash-dspark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="inclusionAI/Ling-3.0-flash-dspark")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("inclusionAI/Ling-3.0-flash-dspark") model = AutoModel.from_pretrained("inclusionAI/Ling-3.0-flash-dspark", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use inclusionAI/Ling-3.0-flash-dspark with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "inclusionAI/Ling-3.0-flash-dspark" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "inclusionAI/Ling-3.0-flash-dspark", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/inclusionAI/Ling-3.0-flash-dspark
- SGLang
How to use inclusionAI/Ling-3.0-flash-dspark 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 "inclusionAI/Ling-3.0-flash-dspark" \ --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": "inclusionAI/Ling-3.0-flash-dspark", "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 "inclusionAI/Ling-3.0-flash-dspark" \ --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": "inclusionAI/Ling-3.0-flash-dspark", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use inclusionAI/Ling-3.0-flash-dspark with Docker Model Runner:
docker model run hf.co/inclusionAI/Ling-3.0-flash-dspark
| { | |
| "architectures": [ | |
| "LingDSparkModel" | |
| ], | |
| "model_type": "qwen3", | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "block_size": 8, | |
| "confidence_head_with_markov": true, | |
| "dtype": "bfloat16", | |
| "embedding_dropout": 0.0, | |
| "enable_confidence_head": true, | |
| "eos_token_id": 156895, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 2560, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6144, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "markov_head_type": "vanilla", | |
| "markov_rank": 256, | |
| "mask_token_id": 156892, | |
| "max_position_embeddings": 262144, | |
| "max_window_layers": 20, | |
| "num_anchors": 512, | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 5, | |
| "num_key_value_heads": 32, | |
| "num_target_layers": 42, | |
| "output_dropout": 0.0, | |
| "pad_token_id": 156892, | |
| "partial_rotary_factor": 1.0, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "partial_rotary_factor": 1.0, | |
| "rope_theta": 6000000.0, | |
| "rope_type": "default" | |
| }, | |
| "rope_theta": 6000000, | |
| "sliding_window": null, | |
| "target_layer_ids": [ | |
| 1, | |
| 11, | |
| 23, | |
| 29, | |
| 35 | |
| ], | |
| "tie_word_embeddings": false, | |
| "transformers_version": "5.12.1", | |
| "vocab_size": 157184 | |
| } | |