Instructions to use saim1212/qwen2_2b_instruct_modified_loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use saim1212/qwen2_2b_instruct_modified_loras with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-VL-2B-Instruct") model = PeftModel.from_pretrained(base_model, "saim1212/qwen2_2b_instruct_modified_loras") - Notebooks
- Google Colab
- Kaggle
Download train_results.json from saim1212/qwen2_2b_instruct_modified_loras: direct link, hf CLI and curl.
- Browser
- Download file 210 Bytes
-
https://huggingface.co/saim1212/qwen2_2b_instruct_modified_loras/resolve/main/train_results.json
- Command line
-
hf download hf://saim1212/qwen2_2b_instruct_modified_loras/train_results.json
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curl -L -o train_results.json https://huggingface.co/saim1212/qwen2_2b_instruct_modified_loras/resolve/main/train_results.json
210 Bytes
| { | |
| "epoch": 25.0, | |
| "total_flos": 1.246578685771776e+17, | |
| "train_loss": 0.15220735648881645, | |
| "train_runtime": 31927.3271, | |
| "train_samples_per_second": 0.392, | |
| "train_steps_per_second": 0.098 | |
| } |