Sentence Similarity
sentence-transformers
Safetensors
Norwegian
Norwegian Nynorsk
Norwegian Bokmål
feature-extraction
dense
custom_code
Eval Results (legacy)
Instructions to use Fremtind/norsbert4-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Fremtind/norsbert4-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Fremtind/norsbert4-large", trust_remote_code=True) sentences = [ "En gruppe barn leker og har det gøy.", "Barn leker på gresset omgitt av sterke farger.", "Barna er sammen.", "Barna leser bøker." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "GptBertModel" | |
| ], | |
| "attention_dropout": 0.0, | |
| "attn_implementation": null, | |
| "auto_map": { | |
| "AutoConfig": "configuration_gptbert.GptBertConfig", | |
| "AutoModel": "modeling_gptbert.GptBertModel", | |
| "AutoModelForCausalLM": "modeling_gptbert.GptBertForCausalLM", | |
| "AutoModelForMaskedLM": "modeling_gptbert.GptBertForMaskedLM", | |
| "AutoModelForMultipleChoice": "modeling_gptbert.GptBertForMultipleChoice", | |
| "AutoModelForQuestionAnswering": "modeling_gptbert.GptBertForQuestionAnswering", | |
| "AutoModelForSequenceClassification": "modeling_gptbert.GptBertForSequenceClassification", | |
| "AutoModelForTokenClassification": "modeling_gptbert.GptBertForTokenClassification" | |
| }, | |
| "bos_token_id": 1, | |
| "classifier_dropout": 0.2, | |
| "deterministic_flash_attn": false, | |
| "embedding_dropout": 0.1, | |
| "eos_token_id": 2, | |
| "global_window_length": 8192, | |
| "hidden_dropout": 0.0, | |
| "hidden_size": 960, | |
| "intermediate_size": 2560, | |
| "layer_norm_eps": 1e-07, | |
| "local_global_ratio": 4, | |
| "local_window_length": 256, | |
| "mask_token_id": 4, | |
| "max_sequence_length": 16384, | |
| "model": "norbert4", | |
| "num_attention_heads": 15, | |
| "num_layers": 28, | |
| "pad_token_id": 3, | |
| "query_key_head_size": 64, | |
| "rope_theta": 160000, | |
| "transformers_version": "4.56.2", | |
| "unk_token_id": 0, | |
| "use_cache": false, | |
| "value_head_size": 64, | |
| "vocab_size": 51200 | |
| } | |