Text Generation
Transformers
Safetensors
llama
llama-factory
full
Generated from Trainer
text-generation-inference
Instructions to use OFA-Sys/MuggleMath_70B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OFA-Sys/MuggleMath_70B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OFA-Sys/MuggleMath_70B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("OFA-Sys/MuggleMath_70B") model = AutoModelForCausalLM.from_pretrained("OFA-Sys/MuggleMath_70B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OFA-Sys/MuggleMath_70B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OFA-Sys/MuggleMath_70B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OFA-Sys/MuggleMath_70B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OFA-Sys/MuggleMath_70B
- SGLang
How to use OFA-Sys/MuggleMath_70B 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 "OFA-Sys/MuggleMath_70B" \ --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": "OFA-Sys/MuggleMath_70B", "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 "OFA-Sys/MuggleMath_70B" \ --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": "OFA-Sys/MuggleMath_70B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OFA-Sys/MuggleMath_70B with Docker Model Runner:
docker model run hf.co/OFA-Sys/MuggleMath_70B
| {"current_steps": 1000, "total_steps": 10818, "loss": 0.5163, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 9.078217455621301e-06, "epoch": 0.28, "percentage": 9.24, "elapsed_time": "6:28:55", "remaining_time": "2 days, 15:38:25"} | |
| {"current_steps": 1000, "total_steps": 10818, "loss": 0.5163, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 9.078217455621301e-06, "epoch": 0.28, "percentage": 9.24, "elapsed_time": "6:28:55", "remaining_time": "2 days, 15:38:26"} | |
| {"current_steps": 1000, "total_steps": 10818, "loss": 0.5163, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 9.078217455621301e-06, "epoch": 0.28, "percentage": 9.24, "elapsed_time": "6:28:55", "remaining_time": "2 days, 15:38:26"} | |
| {"current_steps": 1000, "total_steps": 10818, "loss": 0.5163, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 9.078217455621301e-06, "epoch": 0.28, "percentage": 9.24, "elapsed_time": "6:28:55", "remaining_time": "2 days, 15:38:26"} | |
| {"current_steps": 2000, "total_steps": 10818, "loss": 0.4627, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 8.153661242603551e-06, "epoch": 0.55, "percentage": 18.49, "elapsed_time": "13:00:55", "remaining_time": "2 days, 9:23:06"} | |
| {"current_steps": 2000, "total_steps": 10818, "loss": 0.4627, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 8.153661242603551e-06, "epoch": 0.55, "percentage": 18.49, "elapsed_time": "13:00:55", "remaining_time": "2 days, 9:23:06"} | |
| {"current_steps": 2000, "total_steps": 10818, "loss": 0.4627, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 8.153661242603551e-06, "epoch": 0.55, "percentage": 18.49, "elapsed_time": "13:00:55", "remaining_time": "2 days, 9:23:06"} | |
| {"current_steps": 2000, "total_steps": 10818, "loss": 0.4627, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 8.153661242603551e-06, "epoch": 0.55, "percentage": 18.49, "elapsed_time": "13:00:55", "remaining_time": "2 days, 9:23:06"} | |
| {"current_steps": 3000, "total_steps": 10818, "loss": 0.4393, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 7.229105029585799e-06, "epoch": 0.83, "percentage": 27.73, "elapsed_time": "19:32:29", "remaining_time": "2 days, 2:55:30"} | |
| {"current_steps": 3000, "total_steps": 10818, "loss": 0.4393, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 7.229105029585799e-06, "epoch": 0.83, "percentage": 27.73, "elapsed_time": "19:32:29", "remaining_time": "2 days, 2:55:30"} | |
| {"current_steps": 3000, "total_steps": 10818, "loss": 0.4393, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 7.229105029585799e-06, "epoch": 0.83, "percentage": 27.73, "elapsed_time": "19:32:29", "remaining_time": "2 days, 2:55:30"} | |
| {"current_steps": 3000, "total_steps": 10818, "loss": 0.4393, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 7.229105029585799e-06, "epoch": 0.83, "percentage": 27.73, "elapsed_time": "19:32:29", "remaining_time": "2 days, 2:55:30"} | |
| {"current_steps": 4000, "total_steps": 10818, "loss": 0.3697, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 6.304548816568048e-06, "epoch": 1.11, "percentage": 36.98, "elapsed_time": "1 day, 2:02:03", "remaining_time": "1 day, 20:22:31"} | |
| {"current_steps": 4000, "total_steps": 10818, "loss": 0.3697, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 6.304548816568048e-06, "epoch": 1.11, "percentage": 36.98, "elapsed_time": "1 day, 2:02:03", "remaining_time": "1 day, 20:22:31"} | |
| {"current_steps": 4000, "total_steps": 10818, "loss": 0.3697, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 6.304548816568048e-06, "epoch": 1.11, "percentage": 36.98, "elapsed_time": "1 day, 2:02:03", "remaining_time": "1 day, 20:22:31"} | |
| {"current_steps": 4000, "total_steps": 10818, "loss": 0.3697, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 6.304548816568048e-06, "epoch": 1.11, "percentage": 36.98, "elapsed_time": "1 day, 2:02:03", "remaining_time": "1 day, 20:22:31"} | |
| {"current_steps": 5000, "total_steps": 10818, "loss": 0.2788, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 5.379992603550296e-06, "epoch": 1.39, "percentage": 46.22, "elapsed_time": "1 day, 8:28:55", "remaining_time": "1 day, 13:47:45"} | |
| {"current_steps": 5000, "total_steps": 10818, "loss": 0.2788, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 5.379992603550296e-06, "epoch": 1.39, "percentage": 46.22, "elapsed_time": "1 day, 8:28:55", "remaining_time": "1 day, 13:47:45"} | |
| {"current_steps": 5000, "total_steps": 10818, "loss": 0.2788, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 5.379992603550296e-06, "epoch": 1.39, "percentage": 46.22, "elapsed_time": "1 day, 8:28:55", "remaining_time": "1 day, 13:47:45"} | |
| {"current_steps": 5000, "total_steps": 10818, "loss": 0.2788, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 5.379992603550296e-06, "epoch": 1.39, "percentage": 46.22, "elapsed_time": "1 day, 8:28:55", "remaining_time": "1 day, 13:47:45"} | |
| {"current_steps": 6000, "total_steps": 10818, "loss": 0.2757, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 4.455436390532545e-06, "epoch": 1.66, "percentage": 55.46, "elapsed_time": "1 day, 14:55:00", "remaining_time": "1 day, 7:15:00"} | |
| {"current_steps": 6000, "total_steps": 10818, "loss": 0.2757, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 4.455436390532545e-06, "epoch": 1.66, "percentage": 55.46, "elapsed_time": "1 day, 14:55:00", "remaining_time": "1 day, 7:15:00"} | |
| {"current_steps": 6000, "total_steps": 10818, "loss": 0.2757, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 4.455436390532545e-06, "epoch": 1.66, "percentage": 55.46, "elapsed_time": "1 day, 14:55:00", "remaining_time": "1 day, 7:15:00"} | |
| {"current_steps": 6000, "total_steps": 10818, "loss": 0.2757, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 4.455436390532545e-06, "epoch": 1.66, "percentage": 55.46, "elapsed_time": "1 day, 14:55:00", "remaining_time": "1 day, 7:15:00"} | |
| {"current_steps": 7000, "total_steps": 10818, "loss": 0.2708, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 3.530880177514793e-06, "epoch": 1.94, "percentage": 64.71, "elapsed_time": "1 day, 21:22:31", "remaining_time": "1 day, 0:44:56"} | |
| {"current_steps": 7000, "total_steps": 10818, "loss": 0.2708, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 3.530880177514793e-06, "epoch": 1.94, "percentage": 64.71, "elapsed_time": "1 day, 21:22:31", "remaining_time": "1 day, 0:44:56"} | |
| {"current_steps": 7000, "total_steps": 10818, "loss": 0.2708, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 3.530880177514793e-06, "epoch": 1.94, "percentage": 64.71, "elapsed_time": "1 day, 21:22:31", "remaining_time": "1 day, 0:44:56"} | |
| {"current_steps": 7000, "total_steps": 10818, "loss": 0.2708, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 3.530880177514793e-06, "epoch": 1.94, "percentage": 64.71, "elapsed_time": "1 day, 21:22:31", "remaining_time": "1 day, 0:44:56"} | |
| {"current_steps": 8000, "total_steps": 10818, "loss": 0.1397, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 2.6063239644970415e-06, "epoch": 2.22, "percentage": 73.95, "elapsed_time": "2 days, 3:50:19", "remaining_time": "18:15:36"} | |
| {"current_steps": 8000, "total_steps": 10818, "loss": 0.1397, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 2.6063239644970415e-06, "epoch": 2.22, "percentage": 73.95, "elapsed_time": "2 days, 3:50:19", "remaining_time": "18:15:36"} | |
| {"current_steps": 8000, "total_steps": 10818, "loss": 0.1397, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 2.6063239644970415e-06, "epoch": 2.22, "percentage": 73.95, "elapsed_time": "2 days, 3:50:19", "remaining_time": "18:15:36"} | |
| {"current_steps": 8000, "total_steps": 10818, "loss": 0.1397, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 2.6063239644970415e-06, "epoch": 2.22, "percentage": 73.95, "elapsed_time": "2 days, 3:50:19", "remaining_time": "18:15:36"} | |
| {"current_steps": 9000, "total_steps": 10818, "loss": 0.1026, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 1.6817677514792902e-06, "epoch": 2.5, "percentage": 83.19, "elapsed_time": "2 days, 10:20:13", "remaining_time": "11:47:02"} | |
| {"current_steps": 9000, "total_steps": 10818, "loss": 0.1026, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 1.6817677514792902e-06, "epoch": 2.5, "percentage": 83.19, "elapsed_time": "2 days, 10:20:13", "remaining_time": "11:47:02"} | |
| {"current_steps": 9000, "total_steps": 10818, "loss": 0.1026, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 1.6817677514792902e-06, "epoch": 2.5, "percentage": 83.19, "elapsed_time": "2 days, 10:20:13", "remaining_time": "11:47:02"} | |
| {"current_steps": 9000, "total_steps": 10818, "loss": 0.1026, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 1.6817677514792902e-06, "epoch": 2.5, "percentage": 83.19, "elapsed_time": "2 days, 10:20:13", "remaining_time": "11:47:02"} | |
| {"current_steps": 10000, "total_steps": 10818, "loss": 0.0998, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 7.572115384615385e-07, "epoch": 2.77, "percentage": 92.44, "elapsed_time": "2 days, 16:52:35", "remaining_time": "5:18:24"} | |
| {"current_steps": 10000, "total_steps": 10818, "loss": 0.0998, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 7.572115384615385e-07, "epoch": 2.77, "percentage": 92.44, "elapsed_time": "2 days, 16:52:35", "remaining_time": "5:18:24"} | |
| {"current_steps": 10000, "total_steps": 10818, "loss": 0.0998, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 7.572115384615385e-07, "epoch": 2.77, "percentage": 92.44, "elapsed_time": "2 days, 16:52:35", "remaining_time": "5:18:24"} | |
| {"current_steps": 10000, "total_steps": 10818, "loss": 0.0998, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": 7.572115384615385e-07, "epoch": 2.77, "percentage": 92.44, "elapsed_time": "2 days, 16:52:35", "remaining_time": "5:18:24"} | |
| {"current_steps": 10818, "total_steps": 10818, "loss": null, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": null, "epoch": 3.0, "percentage": 100.0, "elapsed_time": "2 days, 22:10:30", "remaining_time": "0:00:00"} | |
| {"current_steps": 10818, "total_steps": 10818, "loss": null, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": null, "epoch": 3.0, "percentage": 100.0, "elapsed_time": "2 days, 22:10:30", "remaining_time": "0:00:00"} | |
| {"current_steps": 10818, "total_steps": 10818, "loss": null, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": null, "epoch": 3.0, "percentage": 100.0, "elapsed_time": "2 days, 22:10:30", "remaining_time": "0:00:00"} | |
| {"current_steps": 10818, "total_steps": 10818, "loss": null, "eval_loss": null, "predict_loss": null, "reward": null, "learning_rate": null, "epoch": 3.0, "percentage": 100.0, "elapsed_time": "2 days, 22:10:30", "remaining_time": "0:00:00"} | |