Text Generation
Transformers
Safetensors
English
ci
clokai
persona
reasoning
conversational
emotion
tools
Ci-base
ci-instruct-base
Instructions to use clokai/ci-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clokai/ci-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="clokai/ci-base") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("clokai/ci-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use clokai/ci-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "clokai/ci-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "clokai/ci-base", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/clokai/ci-base
- SGLang
How to use clokai/ci-base 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 "clokai/ci-base" \ --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": "clokai/ci-base", "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 "clokai/ci-base" \ --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": "clokai/ci-base", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use clokai/ci-base with Docker Model Runner:
docker model run hf.co/clokai/ci-base
| { | |
| "model_type": "ci", | |
| "architectures": [ | |
| "CiModelForCausalLM" | |
| ], | |
| "hidden_size": 1024, | |
| "num_hidden_layers": 16, | |
| "num_attention_heads": 16, | |
| "num_key_value_heads": 8, | |
| "intermediate_size": 2816, | |
| "vocab_size": 32000, | |
| "max_position_embeddings": 512, | |
| "hidden_dropout_prob": 0.05, | |
| "rms_norm_eps": 1e-06, | |
| "tie_word_embeddings": true, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.40.0", | |
| "use_emotion": true, | |
| "emotion_dim": 512, | |
| "num_emotions": 12, | |
| "use_persona": true, | |
| "persona_dim": 768, | |
| "use_tools": true, | |
| "num_tool_types": 8, | |
| "tool_embed_dim": 512, | |
| "use_reasoning": true, | |
| "reasoning_dim": 768, | |
| "reasoning_steps": 3, | |
| "use_kan": true, | |
| "kan_grid_size": 5, | |
| "use_snn": true, | |
| "snn_layers": [ | |
| 3, | |
| 7, | |
| 11, | |
| 15 | |
| ], | |
| "use_moe": true, | |
| "num_experts": 8, | |
| "num_selected_experts": 2, | |
| "training_step": 74000 | |
| } |