Instructions to use mrm8488/codebert-base-finetuned-stackoverflow-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/codebert-base-finetuned-stackoverflow-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mrm8488/codebert-base-finetuned-stackoverflow-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/codebert-base-finetuned-stackoverflow-ner") model = AutoModelForTokenClassification.from_pretrained("mrm8488/codebert-base-finetuned-stackoverflow-ner") - Notebooks
- Google Colab
- Kaggle
| language: en | |
| datasets: | |
| - https://aclanthology.org/2020.acl-main.443/ | |
| widget: | |
| - text: "I want to create a table and ListView or ArrayList for Android or javascript in Windows 10" | |
| license: mit | |
| # Codebert (base) fine-tuned this [dataset](https://aclanthology.org/2020.acl-main.443/) for NER | |
| ## Eval metrics | |
| eval_accuracy_score = 0.9430622955139325 | |
| eval_precision = 0.6047440699126092 | |
| eval_recall = 0.6100755667506297 | |
| eval_f1 = 0.607398119122257 | |