Instructions to use eek/zephyr-7b-sft-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use eek/zephyr-7b-sft-lora with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("eek/zephyr-7b-sft-lora", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download all_results.json from eek/zephyr-7b-sft-lora: direct link, hf CLI and curl.
- Browser
- Download file 367 Bytes
-
https://huggingface.co/eek/zephyr-7b-sft-lora/resolve/main/all_results.json
- Command line
-
hf download hf://eek/zephyr-7b-sft-lora/all_results.json
-
curl -L -o all_results.json https://huggingface.co/eek/zephyr-7b-sft-lora/resolve/main/all_results.json
367 Bytes
| { | |
| "epoch": 0.36, | |
| "eval_loss": 2.1445040702819824, | |
| "eval_runtime": 1282.8922, | |
| "eval_samples": 20342, | |
| "eval_samples_per_second": 15.856, | |
| "eval_steps_per_second": 0.248, | |
| "train_loss": 2.1917571127414703, | |
| "train_runtime": 41679.8817, | |
| "train_samples": 183082, | |
| "train_samples_per_second": 4.393, | |
| "train_steps_per_second": 0.001 | |
| } |