Instructions to use GenVRadmin/Llamavaad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GenVRadmin/Llamavaad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GenVRadmin/Llamavaad")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("GenVRadmin/Llamavaad") model = AutoModelForCausalLM.from_pretrained("GenVRadmin/Llamavaad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GenVRadmin/Llamavaad with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GenVRadmin/Llamavaad" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GenVRadmin/Llamavaad", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GenVRadmin/Llamavaad
- SGLang
How to use GenVRadmin/Llamavaad 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 "GenVRadmin/Llamavaad" \ --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": "GenVRadmin/Llamavaad", "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 "GenVRadmin/Llamavaad" \ --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": "GenVRadmin/Llamavaad", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GenVRadmin/Llamavaad with Docker Model Runner:
docker model run hf.co/GenVRadmin/Llamavaad
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| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 4.0, | |
| "eval_steps": 0, | |
| "global_step": 2532, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.79, | |
| "learning_rate": 8.025276461295419e-06, | |
| "loss": 0.5594, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 1.58, | |
| "learning_rate": 6.050552922590838e-06, | |
| "loss": 0.4529, | |
| "step": 1000 | |
| }, | |
| { | |
| "epoch": 2.37, | |
| "learning_rate": 4.075829383886256e-06, | |
| "loss": 0.3755, | |
| "step": 1500 | |
| }, | |
| { | |
| "epoch": 3.16, | |
| "learning_rate": 2.101105845181675e-06, | |
| "loss": 0.2917, | |
| "step": 2000 | |
| }, | |
| { | |
| "epoch": 3.95, | |
| "learning_rate": 1.263823064770932e-07, | |
| "loss": 0.1953, | |
| "step": 2500 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "step": 2532, | |
| "total_flos": 5252556024446976.0, | |
| "train_loss": 0.37261163435087763, | |
| "train_runtime": 593262.1709, | |
| "train_samples_per_second": 0.273, | |
| "train_steps_per_second": 0.004 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 2532, | |
| "num_train_epochs": 4, | |
| "save_steps": 1.0, | |
| "total_flos": 5252556024446976.0, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |