Instructions to use mllm-dev/gen_test_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mllm-dev/gen_test_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mllm-dev/gen_test_3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mllm-dev/gen_test_3") model = AutoModelForCausalLM.from_pretrained("mllm-dev/gen_test_3") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mllm-dev/gen_test_3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mllm-dev/gen_test_3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mllm-dev/gen_test_3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mllm-dev/gen_test_3
- SGLang
How to use mllm-dev/gen_test_3 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 "mllm-dev/gen_test_3" \ --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": "mllm-dev/gen_test_3", "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 "mllm-dev/gen_test_3" \ --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": "mllm-dev/gen_test_3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mllm-dev/gen_test_3 with Docker Model Runner:
docker model run hf.co/mllm-dev/gen_test_3
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| "best_metric": 2.0003182888031006, | |
| "best_model_checkpoint": "gen_test/checkpoint-3126", | |
| "epoch": 2.0, | |
| "eval_steps": 500, | |
| "global_step": 3126, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
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| "epoch": 0.32, | |
| "grad_norm": 318423.84375, | |
| "learning_rate": 1.8400511836212414e-05, | |
| "loss": 2.1469, | |
| "step": 500 | |
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| "learning_rate": 1.6801023672424827e-05, | |
| "loss": 1.9333, | |
| "step": 1000 | |
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| "epoch": 0.96, | |
| "grad_norm": 250709.375, | |
| "learning_rate": 1.5201535508637238e-05, | |
| "loss": 1.8887, | |
| "step": 1500 | |
| }, | |
| { | |
| "epoch": 1.0, | |
| "eval_loss": 2.0289978981018066, | |
| "eval_runtime": 56.4689, | |
| "eval_samples_per_second": 177.089, | |
| "eval_steps_per_second": 2.78, | |
| "step": 1563 | |
| }, | |
| { | |
| "epoch": 1.28, | |
| "grad_norm": 241871.234375, | |
| "learning_rate": 1.3602047344849649e-05, | |
| "loss": 1.8677, | |
| "step": 2000 | |
| }, | |
| { | |
| "epoch": 1.6, | |
| "grad_norm": 229897.359375, | |
| "learning_rate": 1.2002559181062061e-05, | |
| "loss": 1.8518, | |
| "step": 2500 | |
| }, | |
| { | |
| "epoch": 1.92, | |
| "grad_norm": 201821.484375, | |
| "learning_rate": 1.0403071017274472e-05, | |
| "loss": 1.8464, | |
| "step": 3000 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_loss": 2.0003182888031006, | |
| "eval_runtime": 56.3343, | |
| "eval_samples_per_second": 177.512, | |
| "eval_steps_per_second": 2.787, | |
| "step": 3126 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 6252, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 4, | |
| "save_steps": 500, | |
| "total_flos": 1.045168128e+17, | |
| "train_batch_size": 64, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |