Sentence Similarity
sentence-transformers
Safetensors
Transformers
Polish
roberta
feature-extraction
information-retrieval
custom_code
text-embeddings-inference
Instructions to use JakubJanusz/roberta_large_v2_ownRep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JakubJanusz/roberta_large_v2_ownRep with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JakubJanusz/roberta_large_v2_ownRep", trust_remote_code=True) sentences = [ "[query]: Jak dożyć 100 lat?", "Trzeba zdrowo się odżywiać i uprawiać sport.", "Trzeba pić alkohol, imprezować i jeździć szybkimi autami.", "Gdy trwała kampania politycy zapewniali, że rozprawią się z zakazem niedzielnego handlu." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use JakubJanusz/roberta_large_v2_ownRep with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("JakubJanusz/roberta_large_v2_ownRep", trust_remote_code=True) model = AutoModel.from_pretrained("JakubJanusz/roberta_large_v2_ownRep", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "sdadas/mmlw-retrieval-roberta-large-v2", | |
| "architectures": [ | |
| "RobertaModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "auto_map": { | |
| "AutoConfig": "sdadas/mmlw-retrieval-roberta-large-v2--configuration_roberta.RobertaConfig", | |
| "AutoModel": "sdadas/mmlw-retrieval-roberta-large-v2--modeling_roberta.RobertaModel", | |
| "AutoModelForSequenceClassification": "sdadas/mmlw-retrieval-roberta-large-v2--modeling_roberta.RobertaForSequenceClassification" | |
| }, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.38.0", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 128001 | |
| } | |