Text Generation
Transformers
Safetensors
cola2
feature-extraction
custom_code
diffusion
continuous-latent
base-model
conversational
Instructions to use ByteDance-Seed/Cola2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ByteDance-Seed/Cola2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ByteDance-Seed/Cola2", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ByteDance-Seed/Cola2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ByteDance-Seed/Cola2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ByteDance-Seed/Cola2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ByteDance-Seed/Cola2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ByteDance-Seed/Cola2
- SGLang
How to use ByteDance-Seed/Cola2 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 "ByteDance-Seed/Cola2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ByteDance-Seed/Cola2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "ByteDance-Seed/Cola2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ByteDance-Seed/Cola2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ByteDance-Seed/Cola2 with Docker Model Runner:
docker model run hf.co/ByteDance-Seed/Cola2
Download config.json from ByteDance-Seed/Cola2: direct link, hf CLI and curl.
- Browser
- Download file 2.16 kB
-
https://huggingface.co/ByteDance-Seed/Cola2/resolve/main/config.json
- Command line
-
hf download hf://ByteDance-Seed/Cola2/config.json
-
curl -L -o config.json https://huggingface.co/ByteDance-Seed/Cola2/resolve/main/config.json
2.16 kB
| { | |
| "architectures": [ | |
| "Cola2ForConditionalGeneration" | |
| ], | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_cola2.Cola2Config", | |
| "AutoModel": "modeling_cola2.Cola2ForConditionalGeneration", | |
| "AutoModelForCausalLM": "modeling_cola2.Cola2ForConditionalGeneration" | |
| }, | |
| "bos_token_id": 151643, | |
| "boundary_score_alpha": 10.0, | |
| "boundary_score_threshold": 0.5, | |
| "cola2_format_version": 1, | |
| "condition_num_attention_heads": 20, | |
| "condition_rope_theta": 500000.0, | |
| "decoder_condition_num_hidden_layers": 2, | |
| "decoder_head_dim": 128, | |
| "decoder_hidden_size": 2560, | |
| "decoder_intermediate_size": 9728, | |
| "decoder_lm_head_bias": true, | |
| "decoder_num_attention_heads": 32, | |
| "decoder_num_hidden_layers": 36, | |
| "decoder_num_key_value_heads": 8, | |
| "decoder_rope_theta": 1000000.0, | |
| "diffusion_time": 1000.0, | |
| "dit_block_size": 8, | |
| "dit_head_dim": 128, | |
| "dit_hidden_size": 2560, | |
| "dit_intermediate_size": 10240, | |
| "dit_layer_norm_eps": 1e-05, | |
| "dit_num_attention_heads": 20, | |
| "dit_num_hidden_layers": 34, | |
| "dit_rope_dim": 96, | |
| "dit_rope_theta": 10000.0, | |
| "duration_hidden_size": 1280, | |
| "encoder_embedding_size": 2560, | |
| "encoder_hidden_size": 1536, | |
| "encoder_intermediate_size": 6144, | |
| "encoder_num_attention_heads": 12, | |
| "encoder_num_hidden_layers": 0, | |
| "encoder_rope_theta": 500000.0, | |
| "eos_token_id": 151643, | |
| "hidden_act": "silu", | |
| "hidden_dropout": 0.0, | |
| "im_end_token_id": 151645, | |
| "im_start_token_id": 151644, | |
| "initializer_range": 0.02, | |
| "latent_block_causal": false, | |
| "latent_block_size": 8, | |
| "latent_decoder_num_hidden_layers": 0, | |
| "latent_dim": 64, | |
| "latent_encoder_num_hidden_layers": 2, | |
| "layer_norm_eps": 1e-06, | |
| "local_position_dim": 128, | |
| "mask_token_id": 151936, | |
| "max_position_embeddings": 32768, | |
| "max_span_length": 8, | |
| "min_span_length": 1, | |
| "model_type": "cola2", | |
| "pad_token_id": 151936, | |
| "pool_num_hidden_layers": 2, | |
| "preset": "cola2", | |
| "rope_theta": 1000000.0, | |
| "scaling_factor": 1.0, | |
| "shifting_factor": 0.0, | |
| "target_compression_rate": 0.5, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "use_variational_encoder": true, | |
| "vocab_size": 151936 | |
| } | |