neuralset.extractors.text.SentenceTransformer¶

class neuralset.extractors.text.SentenceTransformer(*, event_types: Literal['Sentence'] = 'Sentence', aggregation: Literal['single', 'sum', 'mean', 'first', 'middle', 'last', 'cat', 'stack', 'trigger'] = 'single', allow_missing: bool = False, frequency: float = 0.0, language: str = 'english', infra: MapInfra = MapInfra(folder=None, cluster=None, logs='{folder}/logs/{user}/%j', job_name=None, timeout_min=None, nodes=1, tasks_per_node=1, cpus_per_task=None, gpus_per_node=None, mem_gb=None, max_pickle_size_gb=None, slurm_constraint=None, slurm_partition=None, slurm_account=None, slurm_qos=None, slurm_use_srun=False, slurm_additional_parameters=None, conda_env=None, workdir=None, permissions=511, version='0', keep_in_ram=True, max_jobs=128, min_samples_per_job=1, forbid_single_item_computation=False, mode='cached'), model_name: str = 'all-mpnet-base-v2')[source][source]¶: Get embeddings from SentenceTransformers: https://huggingface.co/sentence-transformers.