Text Generation
Transformers
Safetensors
English
mugen
motion
human-motion
text-to-motion
motion-to-text
motion-captioning
motion-generation
autoencoder
gpt2
custom_code
Instructions to use zy22b/MUGEN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zy22b/MUGEN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zy22b/MUGEN", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("zy22b/MUGEN", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zy22b/MUGEN with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zy22b/MUGEN" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zy22b/MUGEN", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/zy22b/MUGEN
- SGLang
How to use zy22b/MUGEN 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 "zy22b/MUGEN" \ --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": "zy22b/MUGEN", "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 "zy22b/MUGEN" \ --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": "zy22b/MUGEN", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use zy22b/MUGEN with Docker Model Runner:
docker model run hf.co/zy22b/MUGEN
| { | |
| "activation_function": "gelu_new", | |
| "alae_activation": "gelu", | |
| "alae_depth": 3, | |
| "alae_dilation_growth_rate": 3, | |
| "alae_dim_feedforward": 2048, | |
| "alae_dropout": 0.05, | |
| "alae_hidden_dim": 512, | |
| "alae_max_decode_len": 256, | |
| "alae_nhead": 8, | |
| "alae_norm": null, | |
| "alae_num_decoder_layers": 4, | |
| "alae_num_encoder_layers": 4, | |
| "alae_num_res_blocks": 2, | |
| "architectures": [ | |
| "MugenForConditionalGeneration" | |
| ], | |
| "attn_pdrop": 0.1, | |
| "auto_map": { | |
| "AutoConfig": "configuration_mugen.MugenConfig", | |
| "AutoModelForCausalLM": "modeling_mugen.MugenForConditionalGeneration" | |
| }, | |
| "bos_token_id": 50256, | |
| "embd_pdrop": 0.1, | |
| "eos_token_id": 50256, | |
| "eval_sample_temperature": 1.0, | |
| "fps": 20, | |
| "initializer_range": 0.02, | |
| "k_latent_slots": 2, | |
| "latent_dim": 512, | |
| "latent_low_rank": 64, | |
| "layer_norm_epsilon": 1e-05, | |
| "length_multiple": 4, | |
| "m2t_max_new_tokens": 64, | |
| "m2t_num_beams": 1, | |
| "m2t_prompt_prefix": "Please describe the following human motion using plain text:", | |
| "model_type": "mugen", | |
| "mot_token": "<MOT>", | |
| "mot_token_id": 50260, | |
| "motion_input_dim": 263, | |
| "n_embd": 768, | |
| "n_head": 12, | |
| "n_inner": null, | |
| "n_layer": 12, | |
| "n_positions": 1024, | |
| "num_cross_attn_layers": 2, | |
| "num_joints": 22, | |
| "pad_token_id": 50256, | |
| "resid_pdrop": 0.1, | |
| "router_delta_scale": 4.0, | |
| "router_eval_tau": 1.5, | |
| "router_hidden": 512, | |
| "router_static_scale": 4.0, | |
| "t2m_prompt_template": "Please generate human motion based on the following textual description: {text} {mot}", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.51.0", | |
| "vocab_size": 50261 | |
| } | |