Instructions to use omarmomen/transformer_base_final_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarmomen/transformer_base_final_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="omarmomen/transformer_base_final_2", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("omarmomen/transformer_base_final_2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- boolq
- cola
- control_raising_control
- control_raising_lexical_content_the
- control_raising_relative_token_position
- lexical_content_the_control
- main_verb_control
- main_verb_lexical_content_the
- main_verb_relative_token_position
- mnli-mm
- mnli
- mrpc
- multirc
- qnli
- qqp
- relative_position_control
- rte
- sst2
- syntactic_category_control
- syntactic_category_lexical_content_the
- syntactic_category_relative_position
- wsc