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
| 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 | |