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 eval_data/lambada.jsonl from ByteDance-Seed/Cola2: direct link, hf CLI and curl.
- Browser
- Download file 2.02 MB
-
https://huggingface.co/ByteDance-Seed/Cola2/resolve/main/eval_data/lambada.jsonl
- Command line
-
hf download hf://ByteDance-Seed/Cola2/eval_data/lambada.jsonl
-
curl -L -o lambada.jsonl https://huggingface.co/ByteDance-Seed/Cola2/resolve/main/eval_data/lambada.jsonl
2.02 MB
File too large to display, you can check the raw version instead.