Instructions to use andstor/bigcode-starcoder2-7b-unit-test-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use andstor/bigcode-starcoder2-7b-unit-test-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoder2-7b") model = PeftModel.from_pretrained(base_model, "andstor/bigcode-starcoder2-7b-unit-test-lora") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from andstor/bigcode-starcoder2-7b-unit-test-lora: direct link, hf CLI and curl.
- Browser
- Download file 277 Bytes
-
https://huggingface.co/andstor/bigcode-starcoder2-7b-unit-test-lora/resolve/main/eval_results.json
- Command line
-
hf download hf://andstor/bigcode-starcoder2-7b-unit-test-lora/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/andstor/bigcode-starcoder2-7b-unit-test-lora/resolve/main/eval_results.json
277 Bytes
| { | |
| "epoch": 2.99835255354201, | |
| "eval_accuracy": 0.7202775795075446, | |
| "eval_loss": 0.6904791593551636, | |
| "eval_runtime": 56.4577, | |
| "eval_samples": 931, | |
| "eval_samples_per_second": 16.49, | |
| "eval_steps_per_second": 8.254, | |
| "perplexity": 1.9946710696011811 | |
| } |