Sentence Similarity
Transformers
Safetensors
sentence_cosenet
feature-extraction
sentence-embeddings
information-retrieval
semantic-search
custom_code
Instructions to use Alverciito/wikipedia_segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alverciito/wikipedia_segmentation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Alverciito/wikipedia_segmentation", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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zero-shot benchmark
alverciitoedbcb21
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fix docstrings
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fix positional encoding error
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fix huggingface model weight missmatch
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fix huggingface model weight missmatch
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fix huggingface model weight missmatch
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fix huggingface model weight missmatch
alverciito4aa1cf7 -
fix huggingface model weight missmatch
alverciito869db96 -
fix huggingface model weight missmatch
alverciito5da73fb -
fix huggingface model missmatch
alverciito34f99b8
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fix model config bug
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fix model config bug
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upload csim labse benchmark
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benchmark last stable version
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bechmark xlm-roberta csim
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bechmark labse, xlm-roberta
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zero shot experiment (fix v4)
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zero shot experiment (fix v3)
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zero shot experiment (fix v2)
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zero shot experiment (fix v2)
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zero shot experiment (fix v1)
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zero shot experiment
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similarity method fixed for two embedding sets
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add zero shot experiment and similarity method
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fix latest import
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finish documentation on readme.md
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l2 normalize get_sentence_embedding
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upload wrapped model.safetensors
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upload wrapped model.safetensors
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add model.py for deployment test
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upload safetensors and refactor research files
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add first set of results
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add first set of results
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add transformers benchmark
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add transformers benchmark
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add original window diff metric for benchmarks
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wikipedia benchmark for proposed algorithm done
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update benchmark script
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benchmark in test dataset
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thresholding benchmark isolated
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Delete src/model/transformers/__pycache__
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Delete src/dlutils/setup/__pycache__
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Delete src/model/cosenet/__pycache__
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Delete src/dlutils/__pycache__
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full inference pipeline
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upload threshold benchmark and inference pipeline
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souce code including custom loss
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upload tensorboard as tensorboard_logs.zip
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