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t12e
/

instructor-base

Sentence Similarity

sentence-transformers

information-retrieval

text-classification

text-clustering

text-semantic-similarity

text-evaluation

prompt-retrieval

feature-extraction

Sentence Similarity

natural_questions

Eval Results (legacy)

Model card Files Files and versions

Instructions to use t12e/instructor-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

sentence-transformers

How to use t12e/instructor-base with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("t12e/instructor-base")

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]

How to use t12e/instructor-base with Transformers:

# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("t12e/instructor-base")
model = AutoModel.from_pretrained("t12e/instructor-base")

Notebooks
Google Colab
Kaggle

instructor-base

444 MB

Ctrl+K

Ctrl+K

1 contributor

History: 5 commits

t12e's picture

updated handler.py

41c2439 almost 3 years ago

1_Pooling
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2_Dense
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__pycache__
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.gitattributes

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README.md

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config.json

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config_sentence_transformers.json

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handler.py

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modules.json

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pytorch_model.bin
Detected Pickle imports (3)
- "collections.OrderedDict",
- "torch.FloatStorage",
- "torch._utils._rebuild_tensor_v2"
What is a pickle import?
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requirements.txt

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sentence_bert_config.json

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special_tokens_map.json

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spiece.model

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tokenizer.json

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tokenizer_config.json

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