Instructions to use dejanai/latent-entity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dejanai/latent-entity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dejanai/latent-entity")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("dejanai/latent-entity") model = AutoModelForCausalLM.from_pretrained("dejanai/latent-entity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dejanai/latent-entity with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dejanai/latent-entity" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dejanai/latent-entity", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dejanai/latent-entity
- SGLang
How to use dejanai/latent-entity 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 "dejanai/latent-entity" \ --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": "dejanai/latent-entity", "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 "dejanai/latent-entity" \ --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": "dejanai/latent-entity", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dejanai/latent-entity with Docker Model Runner:
docker model run hf.co/dejanai/latent-entity
Download generative/tokenizer_config.json from dejanai/latent-entity: direct link, hf CLI and curl.
- Browser
- Download file 727 Bytes
-
https://huggingface.co/dejanai/latent-entity/resolve/main/generative/tokenizer_config.json
- Command line
-
hf download hf://dejanai/latent-entity/generative/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/dejanai/latent-entity/resolve/main/generative/tokenizer_config.json
727 Bytes
| { | |
| "backend": "tokenizers", | |
| "boi_token": "<start_of_image>", | |
| "bos_token": "<bos>", | |
| "clean_up_tokenization_spaces": false, | |
| "eoi_token": "<end_of_image>", | |
| "eos_token": "<eos>", | |
| "image_token": "<image_soft_token>", | |
| "is_local": false, | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "model_specific_special_tokens": { | |
| "boi_token": "<start_of_image>", | |
| "eoi_token": "<end_of_image>", | |
| "image_token": "<image_soft_token>" | |
| }, | |
| "pad_token": "<pad>", | |
| "padding_side": "right", | |
| "sp_model_kwargs": null, | |
| "spaces_between_special_tokens": false, | |
| "tokenizer_class": "GemmaTokenizer", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |