Instructions to use bbunzeck/wanna-pilot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bbunzeck/wanna-pilot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bbunzeck/wanna-pilot")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("bbunzeck/wanna-pilot") model = AutoModelForMultimodalLM.from_pretrained("bbunzeck/wanna-pilot") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bbunzeck/wanna-pilot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bbunzeck/wanna-pilot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bbunzeck/wanna-pilot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bbunzeck/wanna-pilot
- SGLang
How to use bbunzeck/wanna-pilot 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 "bbunzeck/wanna-pilot" \ --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": "bbunzeck/wanna-pilot", "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 "bbunzeck/wanna-pilot" \ --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": "bbunzeck/wanna-pilot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bbunzeck/wanna-pilot with Docker Model Runner:
docker model run hf.co/bbunzeck/wanna-pilot
wanna-pilot
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9860
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9977 | 1.0 | 7813 | 2.0005 |
| 1.9855 | 2.0 | 15626 | 1.9956 |
| 1.9943 | 3.0 | 23439 | 1.9940 |
| 1.9858 | 4.0 | 31252 | 1.9913 |
| 1.9944 | 5.0 | 39065 | 1.9902 |
| 1.9847 | 6.0 | 46878 | 1.9871 |
| 1.9885 | 7.0 | 54691 | 1.9882 |
| 1.9862 | 8.0 | 62504 | 1.9867 |
| 2.0059 | 9.0 | 70317 | 1.9862 |
| 1.9801 | 10.0 | 78130 | 1.9860 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
- Downloads last month
- 164