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 eval_results.json from andstor/Salesforce-codegen-350M-multi-unit-test-ia3: direct link, hf CLI and curl.
- Browser
- Download file 280 Bytes
-
https://huggingface.co/andstor/Salesforce-codegen-350M-multi-unit-test-ia3/resolve/main/eval_results.json
- Command line
-
hf download hf://andstor/Salesforce-codegen-350M-multi-unit-test-ia3/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/andstor/Salesforce-codegen-350M-multi-unit-test-ia3/resolve/main/eval_results.json
280 Bytes
| { | |
| "epoch": 2.995008319467554, | |
| "eval_accuracy": 0.6807527762973363, | |
| "eval_loss": 0.7674357891082764, | |
| "eval_runtime": 32.9422, | |
| "eval_samples": 921, | |
| "eval_samples_per_second": 27.958, | |
| "eval_steps_per_second": 13.994, | |
| "perplexity": 2.1542352519915124 | |
| } |