Instructions to use andstor/Salesforce-codegen-350M-multi-unit-test-ia3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use andstor/Salesforce-codegen-350M-multi-unit-test-ia3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-multi") model = PeftModel.from_pretrained(base_model, "andstor/Salesforce-codegen-350M-multi-unit-test-ia3") - Notebooks
- Google Colab
- Kaggle
Download train_results.json from andstor/Salesforce-codegen-350M-multi-unit-test-ia3: direct link, hf CLI and curl.
- Browser
- Download file 246 Bytes
-
https://huggingface.co/andstor/Salesforce-codegen-350M-multi-unit-test-ia3/resolve/main/train_results.json
- Command line
-
hf download hf://andstor/Salesforce-codegen-350M-multi-unit-test-ia3/train_results.json
-
curl -L -o train_results.json https://huggingface.co/andstor/Salesforce-codegen-350M-multi-unit-test-ia3/resolve/main/train_results.json
246 Bytes
| { | |
| "epoch": 2.995008319467554, | |
| "total_flos": 2.325536422179635e+16, | |
| "train_loss": 0.7775403798068011, | |
| "train_runtime": 1848.9044, | |
| "train_samples": 7211, | |
| "train_samples_per_second": 11.7, | |
| "train_steps_per_second": 0.73 | |
| } |