Instructions to use IDEA-FinAI/chartmoe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDEA-FinAI/chartmoe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="IDEA-FinAI/chartmoe", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("IDEA-FinAI/chartmoe", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use IDEA-FinAI/chartmoe with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "IDEA-FinAI/chartmoe" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "IDEA-FinAI/chartmoe", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/IDEA-FinAI/chartmoe
- SGLang
How to use IDEA-FinAI/chartmoe 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 "IDEA-FinAI/chartmoe" \ --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": "IDEA-FinAI/chartmoe", "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 "IDEA-FinAI/chartmoe" \ --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": "IDEA-FinAI/chartmoe", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use IDEA-FinAI/chartmoe with Docker Model Runner:
docker model run hf.co/IDEA-FinAI/chartmoe
| { | |
| "architectures": [ | |
| "ChartMoEForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_chartmoe.ChartMoEConfig", | |
| "AutoModel": "modeling_chartmoe.ChartMoEForCausalLM", | |
| "AutoModelForCausalLM": "modeling_chartmoe.ChartMoEForCausalLM" | |
| }, | |
| "attn_implementation": "flash_attention_2", | |
| "bias": false, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_length": 4096, | |
| "max_position_embeddings": 32768, | |
| "model_type": "chartmoe", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 2, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "factor": 1.0, | |
| "type": "dynamic" | |
| }, | |
| "rope_theta": 1000000, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.33.1", | |
| "use_cache": false, | |
| "vocab_size": 92544, | |
| "img_size": 490, | |
| "num_experts": 4, | |
| "num_selected": 2 | |
| } | |