Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:5000000
loss:combine_dstilationLoss_studentLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1") sentences = [ "ما هو كور يعني", "تعريف cor . : وحدة قياس سعة عبرية وفينيقية قديمة .", "رفعت منظمة صندوق ادخار الموظفين ( EPFO ) الحد الأدنى للراتب إلى 15000 روبية من 6500 روبية في وقت سابق .", "شكل الجمع بين الجلطة - o يعني _ _ . صيغة الجمع embol - o تعني _ _ . اللاحقة التي تعني أداة قياس الضغط هي _ _ . لاحقة غير كلها تعني صغيرة هي _ _ . اللاحقة التي تعني التصلب هي _ _ ." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config.json from hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1: direct link, hf CLI and curl.
- Browser
- Download file 742 Bytes
-
https://huggingface.co/hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1/resolve/main/config.json
- Command line
-
hf download hf://hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1/config.json
-
curl -L -o config.json https://huggingface.co/hatemestinbejaia/R3mmarco-Arabic-mMiniLML-bi-encoder-KD-v1/resolve/main/config.json
742 Bytes
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 384, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "is_decoder": false, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.18.0", | |
| "type_vocab_size": 2, | |
| "use_cache": false, | |
| "vocab_size": 250037 | |
| } | |