Text Generation
Transformers
PyTorch
Safetensors
English
diffusionLM
feature-extraction
DiffusionLLM
custom_code
Instructions to use codewithdark/DiffusionLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codewithdark/DiffusionLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="codewithdark/DiffusionLM", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("codewithdark/DiffusionLM", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use codewithdark/DiffusionLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "codewithdark/DiffusionLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codewithdark/DiffusionLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/codewithdark/DiffusionLM
- SGLang
How to use codewithdark/DiffusionLM 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 "codewithdark/DiffusionLM" \ --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": "codewithdark/DiffusionLM", "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 "codewithdark/DiffusionLM" \ --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": "codewithdark/DiffusionLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use codewithdark/DiffusionLM with Docker Model Runner:
docker model run hf.co/codewithdark/DiffusionLM
| { | |
| "architectures": [ | |
| "DiffusionLLM" | |
| ], | |
| "auto_map": { | |
| "AutoModel": "modeling_DiffusionLLM.DiffusionLLM", | |
| "AutoModelForCausalLM": "modeling_DiffusionLLM.DiffusionLLM", | |
| "AutoConfig": "modeling_DiffusionLLM.DiffusionConfig" | |
| }, | |
| "attention_probs_dropout_prob": 0.1, | |
| "eos_token_id": 50256, | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 256, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "layer_norm_eps": 1e-12, | |
| "mask_token_id": 50257, | |
| "max_position_embeddings": 256, | |
| "model_type": "diffusionLM", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 4, | |
| "num_timesteps": 100, | |
| "pad_token_id": 50258, | |
| "time_embed_dim": 128, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.48.3", | |
| "vocab_size": 50259 | |
| } | |