quangtqv / bi_encoder_tool_learning_9_5_5024_v4.1

huggingface.co
Total runs: 87
24-hour runs: 0
7-day runs: 24
30-day runs: 22
Model's Last Updated: May 09 2024
sentence-similarity

Introduction of bi_encoder_tool_learning_9_5_5024_v4.1

Model Details of bi_encoder_tool_learning_9_5_5024_v4.1

quangtqv/bi_encoder_tool_learning_9_5_5024_v4.1

This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.

Usage (Sentence-Transformers)

Using this model becomes easy when you have sentence-transformers installed:

pip install -U sentence-transformers

Then you can use the model like this:

from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('quangtqv/bi_encoder_tool_learning_9_5_5024_v4.1')
embeddings = model.encode(sentences)
print(embeddings)
Evaluation Results

For an automated evaluation of this model, see the Sentence Embeddings Benchmark : https://seb.sbert.net

Full Model Architecture
SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)
Citing & Authors

Runs of quangtqv bi_encoder_tool_learning_9_5_5024_v4.1 on huggingface.co

87
Total runs
0
24-hour runs
10
3-day runs
24
7-day runs
22
30-day runs

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bi_encoder_tool_learning_9_5_5024_v4.1 install

bi_encoder_tool_learning_9_5_5024_v4.1 is an open source model from GitHub that offers a free installation service, and any user can find bi_encoder_tool_learning_9_5_5024_v4.1 on GitHub to install. At the same time, huggingface.co provides the effect of bi_encoder_tool_learning_9_5_5024_v4.1 install, users can directly use bi_encoder_tool_learning_9_5_5024_v4.1 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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quangtqv
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