Instructions to use codistai/codeBERT-small-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codistai/codeBERT-small-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="codistai/codeBERT-small-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("codistai/codeBERT-small-v2") model = AutoModelForMaskedLM.from_pretrained("codistai/codeBERT-small-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: openrail
datasets:
- fka/awesome-chatgpt-prompts
- gsdf/EasyNegative
- Nerfgun3/bad_prompt
- SirNeural/flan_v2
language:
- ar
- ay
metrics:
- accuracy
- character
- code_eval
- chrf
library_name: adapter-transformers
pipeline_tag: text-to-image
tags:
- code
- legal