Sentence Similarity
sentence-transformers
Safetensors
Transformers
English
bert_hash
feature-extraction
custom_code
Instructions to use NeuML/bert-hash-pico-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NeuML/bert-hash-pico-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NeuML/bert-hash-pico-embeddings", trust_remote_code=True) sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use NeuML/bert-hash-pico-embeddings with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("NeuML/bert-hash-pico-embeddings", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "BertHashModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "auto_map": { | |
| "AutoConfig": "configuration_bert_hash.BertHashConfig", | |
| "AutoModel": "modeling_bert_hash.BertHashModel", | |
| "AutoModelForMaskedLM": "modeling_bert_hash.BertHashForMaskedLM", | |
| "AutoModelForSequenceClassification": "modeling_bert_hash.BertHashForSequenceClassification" | |
| }, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 80, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 320, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert_hash", | |
| "num_attention_heads": 2, | |
| "num_hidden_layers": 2, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "projections": 8, | |
| "transformers_version": "4.57.3", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 30522 | |
| } | |