Text Generation
PEFT
Safetensors
English
lora
sports-science
athlete-monitoring
structured-generation
conversational
Instructions to use tyhob/loadbrief with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tyhob/loadbrief with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "tyhob/loadbrief") - Notebooks
- Google Colab
- Kaggle
Download training_config.json from tyhob/loadbrief: direct link, hf CLI and curl.
- Browser
- Download file 271 Bytes
-
https://huggingface.co/tyhob/loadbrief/resolve/main/training_config.json
- Command line
-
hf download hf://tyhob/loadbrief/training_config.json
-
curl -L -o training_config.json https://huggingface.co/tyhob/loadbrief/resolve/main/training_config.json
271 Bytes
| { | |
| "model_name": "meta-llama/Meta-Llama-3-8B-Instruct", | |
| "lora_rank": 32, | |
| "effective_batch": 32, | |
| "learning_rate": 0.0002, | |
| "epochs": 1, | |
| "max_length": 512, | |
| "train_examples": 20000, | |
| "training_minutes": 1719.6, | |
| "trl_version": "1.5.1", | |
| "device": "mps_48gb" | |
| } |