Instructions to use QiHoaran/ArchiCell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use QiHoaran/ArchiCell with PEFT:
Task type is invalid.
- Transformers
How to use QiHoaran/ArchiCell with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="QiHoaran/ArchiCell")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("QiHoaran/ArchiCell", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use QiHoaran/ArchiCell with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "QiHoaran/ArchiCell" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QiHoaran/ArchiCell", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/QiHoaran/ArchiCell
- SGLang
How to use QiHoaran/ArchiCell 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 "QiHoaran/ArchiCell" \ --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": "QiHoaran/ArchiCell", "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 "QiHoaran/ArchiCell" \ --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": "QiHoaran/ArchiCell", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use QiHoaran/ArchiCell with Docker Model Runner:
docker model run hf.co/QiHoaran/ArchiCell
| { | |
| "add_prefix_space": false, | |
| "audio_bos_token": "<|audio_start|>", | |
| "audio_eos_token": "<|audio_end|>", | |
| "audio_token": "<|audio_pad|>", | |
| "backend": "tokenizers", | |
| "bos_token": "<bos>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<eos>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<input>", | |
| "<output>", | |
| "<3d_begin>", | |
| "<z_0>", | |
| "<z_1>", | |
| "<z_2>", | |
| "<z_3>", | |
| "<z_4>", | |
| "<z_5>", | |
| "<z_6>", | |
| "<z_7>", | |
| "<n_0>", | |
| "<n_1>", | |
| "<n_2>", | |
| "<n_3>", | |
| "<n_4>", | |
| "<n_5>", | |
| "<n_6>", | |
| "<n_7>", | |
| "<n_8>", | |
| "<n_9>", | |
| "<n_10>", | |
| "<n_11>", | |
| "<n_12>", | |
| "<n_13>", | |
| "<n_14>", | |
| "<n_15>", | |
| "<n_16>", | |
| "<n_17>", | |
| "<n_18>", | |
| "<n_19>", | |
| "<n_20>", | |
| "<n_21>", | |
| "<n_22>", | |
| "<n_23>", | |
| "<n_24>", | |
| "<n_25>", | |
| "<n_26>", | |
| "<n_27>", | |
| "<n_28>", | |
| "<n_29>", | |
| "<n_30>", | |
| "<n_31>", | |
| "<n_32>", | |
| "<n_33>", | |
| "<n_34>", | |
| "<n_35>", | |
| "<n_36>", | |
| "<n_37>", | |
| "<n_38>", | |
| "<n_39>", | |
| "<n_40>", | |
| "<n_41>", | |
| "<n_42>", | |
| "<n_43>", | |
| "<n_44>", | |
| "<n_45>", | |
| "<n_46>", | |
| "<n_47>", | |
| "<n_48>", | |
| "<n_49>", | |
| "<n_50>", | |
| "<n_51>", | |
| "<n_52>", | |
| "<n_53>", | |
| "<n_54>", | |
| "<n_55>", | |
| "<n_56>", | |
| "<n_57>", | |
| "<n_58>", | |
| "<n_59>", | |
| "<n_60>", | |
| "<n_61>", | |
| "<n_62>", | |
| "<n_63>", | |
| "<n_64>", | |
| "<c_0>", | |
| "<c_1>", | |
| "<c_2>", | |
| "<c_3>", | |
| "<c_4>", | |
| "<c_5>", | |
| "<c_6>", | |
| "<c_7>", | |
| "<c_8>", | |
| "<c_9>", | |
| "<c_10>", | |
| "<c_11>", | |
| "<c_12>", | |
| "<c_13>", | |
| "<c_14>", | |
| "<c_15>", | |
| "<c_16>", | |
| "<c_17>", | |
| "<c_18>", | |
| "<c_19>", | |
| "<c_20>", | |
| "<c_21>", | |
| "<c_22>", | |
| "<c_23>", | |
| "<c_24>", | |
| "<c_25>", | |
| "<c_26>", | |
| "<c_27>", | |
| "<c_28>", | |
| "<c_29>", | |
| "<c_30>", | |
| "<c_31>", | |
| "<c_32>", | |
| "<c_33>", | |
| "<c_34>", | |
| "<c_35>", | |
| "<c_36>", | |
| "<c_37>", | |
| "<c_38>", | |
| "<c_39>", | |
| "<c_40>", | |
| "<c_41>", | |
| "<c_42>", | |
| "<c_43>", | |
| "<c_44>", | |
| "<c_45>", | |
| "<c_46>", | |
| "<c_47>", | |
| "<c_48>", | |
| "<c_49>", | |
| "<c_50>", | |
| "<c_51>", | |
| "<c_52>", | |
| "<c_53>", | |
| "<c_54>", | |
| "<c_55>", | |
| "<c_56>", | |
| "<c_57>", | |
| "<c_58>", | |
| "<c_59>", | |
| "<c_60>", | |
| "<c_61>", | |
| "<c_62>", | |
| "<c_63>", | |
| "<3d_end>" | |
| ], | |
| "image_token": "<|image_pad|>", | |
| "is_local": true, | |
| "model_max_length": 262144, | |
| "model_specific_special_tokens": { | |
| "audio_bos_token": "<|audio_start|>", | |
| "audio_eos_token": "<|audio_end|>", | |
| "audio_token": "<|audio_pad|>", | |
| "image_token": "<|image_pad|>", | |
| "video_token": "<|video_pad|>", | |
| "vision_bos_token": "<|vision_start|>", | |
| "vision_eos_token": "<|vision_end|>" | |
| }, | |
| "pad_token": "<pad>", | |
| "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": null, | |
| "video_token": "<|video_pad|>", | |
| "vision_bos_token": "<|vision_start|>", | |
| "vision_eos_token": "<|vision_end|>" | |
| } | |