Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Rust
ONNX
Safetensors
OpenVINO
Transformers
Transformers.js
English
nomic_bert
feature-extraction
mteb
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use RedHatAI/nomic-embed-text-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use RedHatAI/nomic-embed-text-v1.5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RedHatAI/nomic-embed-text-v1.5", 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 RedHatAI/nomic-embed-text-v1.5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("RedHatAI/nomic-embed-text-v1.5", trust_remote_code=True) model = AutoModel.from_pretrained("RedHatAI/nomic-embed-text-v1.5", trust_remote_code=True, device_map="auto") - Transformers.js
How to use RedHatAI/nomic-embed-text-v1.5 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'RedHatAI/nomic-embed-text-v1.5'); - Notebooks
- Google Colab
- Kaggle
update config.json to use local configuration_hf_nomic_bert and modeling_hf_nomic_bert
Browse files- config.json +7 -7
config.json
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],
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"attn_pdrop": 0.0,
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"auto_map": {
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"AutoConfig": "
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"AutoModel": "
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"AutoModelForMaskedLM": "
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"AutoModelForSequenceClassification": "
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"AutoModelForMultipleChoice": "
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"AutoModelForQuestionAnswering": "
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"AutoModelForTokenClassification": "
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},
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"bos_token_id": null,
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"causal": false,
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],
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"attn_pdrop": 0.0,
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"auto_map": {
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"AutoConfig": "configuration_hf_nomic_bert.NomicBertConfig",
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"AutoModel": "modeling_hf_nomic_bert.NomicBertModel",
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"AutoModelForMaskedLM": "modeling_hf_nomic_bert.NomicBertForPreTraining",
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"AutoModelForSequenceClassification": "modeling_hf_nomic_bert.NomicBertForSequenceClassification",
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"AutoModelForMultipleChoice": "modeling_hf_nomic_bert.NomicBertForMultipleChoice",
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"AutoModelForQuestionAnswering": "modeling_hf_nomic_bert.NomicBertForQuestionAnswering",
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"AutoModelForTokenClassification": "modeling_hf_nomic_bert.NomicBertForTokenClassification"
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},
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"bos_token_id": null,
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"causal": false,
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