Text Generation
Transformers
Safetensors
PEFT
maeyen-trust-risk-assistant
lora
maeyen
risk-assessment
trust-score
dispute-management
evidence-review
Instructions to use tarvico/maeyen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarvico/maeyen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tarvico/maeyen")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("tarvico/maeyen", dtype="auto") - PEFT
How to use tarvico/maeyen with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tarvico/maeyen with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tarvico/maeyen" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tarvico/maeyen", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tarvico/maeyen
- SGLang
How to use tarvico/maeyen 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 "tarvico/maeyen" \ --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": "tarvico/maeyen", "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 "tarvico/maeyen" \ --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": "tarvico/maeyen", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tarvico/maeyen with Docker Model Runner:
docker model run hf.co/tarvico/maeyen
| # How to Upload to Hugging Face Hub (Web UI) | |
| ## IMPORTANT FIRST STEP: | |
| - **DO NOT UPLOAD `PRIVATE_MODEL_TRAINING_NOTES.md` TO HUGGING FACE!** This file stays internal only. | |
| ## Step 1: Create a New Model Repository on Hugging Face | |
| 1. Go to https://huggingface.co/ | |
| 2. Log in with your `tarvico` account | |
| 3. Click on your profile picture → "New Model" | |
| 4. Fill in the details: | |
| - **Model name**: `maeyen-ai-model` | |
| - **Owner**: `tarvico` | |
| - **License**: Choose one (e.g., MIT, Apache-2.0) | |
| - **Task**: Text Generation | |
| - **Library**: transformers, peft | |
| - **Language**: English | |
| - **Visibility**: Choose "Private" if possible to avoid accidental exposure | |
| 5. Click "Create model" | |
| ## Step 2: Upload All Files Except PRIVATE_MODEL_TRAINING_NOTES.md | |
| On your new model page (https://huggingface.co/tarvico/maeyen-ai-model): | |
| 1. Click "Files and versions" tab | |
| 2. Click "Add file" → "Upload files" | |
| 3. Upload **ALL** files in this folder **EXCEPT `PRIVATE_MODEL_TRAINING_NOTES.md`**: | |
| - `README.md` (with YAML metadata at top) | |
| - `config.json` | |
| - `generation_config.json` | |
| - `adapter_config.json` | |
| - `adapter_model.safetensors` (IMPORTANT! This is the LoRA weights file) | |
| - `requirements.txt` | |
| - `train.py` | |
| - `inference.py` | |
| - `tokenizer_config.json` | |
| - `.gitattributes` (CRITICAL! Don't skip this!) | |
| - `maeyen_examples.jsonl` | |
| - `generate_dummy_weights.py` | |
| - `UPLOAD_GUIDE.md` | |
| 4. Add a commit message like "Initial Maeyen Trust & Risk Assistant" | |
| 5. Click "Commit changes" | |
| ## Step 3: Later, Replace Dummy Weights with Real Ones | |
| When you have real data and can train properly: | |
| 1. Replace `adapter_model.safetensors` with your trained weights | |
| 2. Commit the new file | |
| ## Critical Reminders: | |
| - **NEVER UPLOAD `PRIVATE_MODEL_TRAINING_NOTES.md` TO PUBLIC/PRIVATE HUGGING FACE REPO** | |
| - Keep all base model details internal only | |
| - If making repo public, double-check license compliance for base model | |
| - All public content uses "Maeyen Trust & Risk Assistant" only | |