Sentence Similarity
sentence-transformers
ONNX
Safetensors
nomic_bert
feature-extraction
dense
Generated from Trainer
dataset_size:6294
loss:MultipleNegativesRankingLoss
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use asmud/nomic-embed-indonesian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use asmud/nomic-embed-indonesian with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("asmud/nomic-embed-indonesian", trust_remote_code=True) sentences = [ "search_query: ['Ketua', 'Umum', 'organisasi', 'apakah', 'Syamsurizal', '?']", "search_document: ['Ketua', 'Umum', 'Pengurus', 'Besar', 'Persatuan', 'Sepak', 'Takraw', 'Seluruh', 'Indonesia', '(', 'PB', 'Persetasi', ')', 'Syamsurizal', 'mengatakan', ',', 'kejurnas', 'kali', 'ini', 'tak', 'hanya', 'dimanfaatkan', 'sebagai', 'sarana', 'mencari', 'bibit', 'baru', '.', '\"', 'Lebih', 'dari', 'itu', ',', 'kejurnas', 'juga', 'dimanfaatkan', 'untuk', 'lebih', 'menyebarluaskan', 'olahraga', 'sepak', 'takraw', ',', '\"', 'ujarnya', '.']", "clustering: Dalam sebuah doa, kucoba merayu Tuhan. Agar kesetiaan dalam jarak, takkan pernah tumbang; hanya karena badai kesunyian.", "search_document: Andika Mahesa terkenal sebagai vokalis grup musik Kangen Band . Selain itu , Andika tampak dekat dengan sejumlah perempuan . Hal tersebut membuatnya mendapat julukan ' Babang Tamvan ' . Mulanya , Andika menganggap sebutan tersebut sebagai musibah . Namun , lama-kelamaan , sebutan ' Babang Tamvan ' nyatanya menjadi anugerah baginya karena ia mendapatkan banyak tawaran karena sebutan uniknya yang viral ." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "activation_function": "swiglu", | |
| "architectures": [ | |
| "NomicBertModel" | |
| ], | |
| "attn_pdrop": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_hf_nomic_bert.NomicBertConfig", | |
| "AutoModel": "modeling_hf_nomic_bert.NomicBertModel", | |
| "AutoModelForMaskedLM": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertForPreTraining", | |
| "AutoModelForMultipleChoice": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertForMultipleChoice", | |
| "AutoModelForQuestionAnswering": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertForQuestionAnswering", | |
| "AutoModelForSequenceClassification": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertForSequenceClassification", | |
| "AutoModelForTokenClassification": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertForTokenClassification" | |
| }, | |
| "bos_token_id": null, | |
| "causal": false, | |
| "dense_seq_output": true, | |
| "embd_pdrop": 0.0, | |
| "eos_token_id": null, | |
| "fused_bias_fc": true, | |
| "fused_dropout_add_ln": true, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-12, | |
| "max_trained_positions": 2048, | |
| "mlp_fc1_bias": false, | |
| "mlp_fc2_bias": false, | |
| "model_type": "nomic_bert", | |
| "n_embd": 768, | |
| "n_head": 12, | |
| "n_inner": 3072, | |
| "n_layer": 12, | |
| "n_positions": 8192, | |
| "pad_vocab_size_multiple": 64, | |
| "parallel_block": false, | |
| "parallel_block_tied_norm": false, | |
| "prenorm": false, | |
| "qkv_proj_bias": false, | |
| "reorder_and_upcast_attn": false, | |
| "resid_pdrop": 0.0, | |
| "rotary_emb_base": 1000, | |
| "rotary_emb_fraction": 1.0, | |
| "rotary_emb_interleaved": false, | |
| "rotary_emb_scale_base": null, | |
| "rotary_scaling_factor": null, | |
| "scale_attn_by_inverse_layer_idx": false, | |
| "scale_attn_weights": true, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.0, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.54.1", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "use_flash_attn": true, | |
| "use_rms_norm": false, | |
| "use_xentropy": true, | |
| "vocab_size": 30528 | |
| } | |