Instructions to use SushantGautam/CodeGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SushantGautam/CodeGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SushantGautam/CodeGeneration")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SushantGautam/CodeGeneration") model = AutoModelForMaskedLM.from_pretrained("SushantGautam/CodeGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from SushantGautam/CodeGeneration: direct link, hf CLI and curl.
- Browser
- Download file 265 Bytes
-
https://huggingface.co/SushantGautam/CodeGeneration/resolve/main/eval_results.json
- Command line
-
hf download hf://SushantGautam/CodeGeneration/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/SushantGautam/CodeGeneration/resolve/main/eval_results.json
265 Bytes
| { | |
| "epoch": 10.0, | |
| "eval_accuracy": 0.4444444444444444, | |
| "eval_loss": 3.502009630203247, | |
| "eval_runtime": 0.2824, | |
| "eval_samples": 176, | |
| "eval_samples_per_second": 623.144, | |
| "eval_steps_per_second": 77.893, | |
| "perplexity": 33.18206868621658 | |
| } |