Text Generation
Transformers
hyperlm_qwen3
hypergraph
large-language-models
qwen3
projector
hyper-align
hypergraph-as-language
Instructions to use MengqiLei/hyper-align with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MengqiLei/hyper-align with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MengqiLei/hyper-align")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("MengqiLei/hyper-align", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use MengqiLei/hyper-align with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MengqiLei/hyper-align" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MengqiLei/hyper-align", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MengqiLei/hyper-align
- SGLang
How to use MengqiLei/hyper-align 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 "MengqiLei/hyper-align" \ --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": "MengqiLei/hyper-align", "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 "MengqiLei/hyper-align" \ --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": "MengqiLei/hyper-align", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MengqiLei/hyper-align with Docker Model Runner:
docker model run hf.co/MengqiLei/hyper-align
File size: 2,081 Bytes
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"architectures": [
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"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 151643,
"consistency_start_step": 0,
"consistency_warmup_steps": 0,
"eos_token_id": 151645,
"freeze_mm_mlp_adapter": false,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 4096,
"htp_num_layers": 1,
"htp_semantic_core_dim": 384,
"htp_structure_sidecar_dim": 64,
"hypergraph_semantic_dim": 1024,
"hypergraph_structure_dim": 24,
"initializer_range": 0.02,
"intermediate_size": 12288,
"lambda_ord": 0.01,
"lambda_rel": 0.01,
"layer_types": [
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"max_position_embeddings": 40960,
"max_window_layers": 36,
"mm_hidden_size": 1048,
"mm_projector_type": "htp",
"mm_use_graph_special_token": false,
"mm_use_graph_start_end": false,
"model_type": "hyperlm_qwen3",
"num_attention_heads": 32,
"num_hidden_layers": 36,
"num_key_value_heads": 8,
"projector_incidence_mode": "sample_real",
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 1000000,
"sliding_window": null,
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.53.0",
"tune_mm_mlp_adapter": true,
"use_cache": true,
"use_mm_proj": true,
"use_sliding_window": false,
"vocab_size": 151936
}
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