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 train_results.json from SushantGautam/CodeGeneration: direct link, hf CLI and curl.
- Browser
- Download file 194 Bytes
-
https://huggingface.co/SushantGautam/CodeGeneration/resolve/main/train_results.json
- Command line
-
hf download hf://SushantGautam/CodeGeneration/train_results.json
-
curl -L -o train_results.json https://huggingface.co/SushantGautam/CodeGeneration/resolve/main/train_results.json
194 Bytes
| { | |
| "epoch": 10.0, | |
| "train_loss": 3.5042898788946366, | |
| "train_runtime": 613.1863, | |
| "train_samples": 3507, | |
| "train_samples_per_second": 57.193, | |
| "train_steps_per_second": 7.159 | |
| } |