Instructions to use ECE-Software/tribunal-agent-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ECE-Software/tribunal-agent-v3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ECE-Software/gemma-3-270m") model = PeftModel.from_pretrained(base_model, "ECE-Software/tribunal-agent-v3") - Transformers
How to use ECE-Software/tribunal-agent-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ECE-Software/tribunal-agent-v3") 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("ECE-Software/tribunal-agent-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ECE-Software/tribunal-agent-v3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ECE-Software/tribunal-agent-v3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ECE-Software/tribunal-agent-v3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ECE-Software/tribunal-agent-v3
- SGLang
How to use ECE-Software/tribunal-agent-v3 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 "ECE-Software/tribunal-agent-v3" \ --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": "ECE-Software/tribunal-agent-v3", "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 "ECE-Software/tribunal-agent-v3" \ --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": "ECE-Software/tribunal-agent-v3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ECE-Software/tribunal-agent-v3 with Docker Model Runner:
docker model run hf.co/ECE-Software/tribunal-agent-v3
Download tokenizer_config.json from ECE-Software/tribunal-agent-v3: direct link, hf CLI and curl.
- Browser
- Download file 730 Bytes
-
https://huggingface.co/ECE-Software/tribunal-agent-v3/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ECE-Software/tribunal-agent-v3/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ECE-Software/tribunal-agent-v3/resolve/main/tokenizer_config.json
730 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": true, | |
| "local_files_only": 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": "left", | |
| "sp_model_kwargs": null, | |
| "spaces_between_special_tokens": false, | |
| "tokenizer_class": "GemmaTokenizer", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |