Upload model
Browse files- README.md +8 -11
- config.json +5 -4
- pytorch_model.bin +1 -1
- tokenizer_config.json +1 -1
README.md
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---
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license: apache-2.0
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library_name:
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tags:
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- token-classification
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- ner
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- named-entity-recognition
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pipeline_tag: token-classification
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datasets:
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- DFKI-SLT/few-nerd
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language:
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- en
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---
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# SpanMarker for Named Entity Recognition
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be
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## Usage
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pip install span_marker
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```
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You can then run inference
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```python
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from span_marker import SpanMarkerModel
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# Download from
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model = SpanMarkerModel.from_pretrained("
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# Run inference
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entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")
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```
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See the [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) repository for documentation and additional information on this
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---
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license: apache-2.0
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library_name: span-marker
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tags:
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- span-marker
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- token-classification
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- ner
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- named-entity-recognition
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pipeline_tag: token-classification
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---
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# SpanMarker for Named Entity Recognition
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be usedfor Named Entity Recognition. In particular, this SpanMarker model uses [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) as the underlying encoder.
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## Usage
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pip install span_marker
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```
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You can then run inference with this model like so:
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```python
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from span_marker import SpanMarkerModel
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# Download from the 🤗 Hub
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model = SpanMarkerModel.from_pretrained("span_marker_model_name")
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# Run inference
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entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")
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```
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See the [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) repository for documentation and additional information on this library.
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config.json
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{
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"_name_or_path": "models\\bt-coarse-
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"architectures": [
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"SpanMarkerModel"
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],
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"use_cache": true,
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"vocab_size": 30524
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},
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"entity_max_length":
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"marker_max_length":
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"model_max_length":
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"model_max_length_default": 512,
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"model_type": "span-marker",
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"torch_dtype": "float32",
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"transformers_version": "4.27.2",
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"vocab_size": 30524
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{
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"_name_or_path": "models\\bt-full-coarse-1\\checkpoint-final",
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"architectures": [
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"SpanMarkerModel"
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],
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"use_cache": true,
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"vocab_size": 30524
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},
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"entity_max_length": 8,
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"marker_max_length": 128,
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"model_max_length": 256,
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"model_max_length_default": 512,
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"model_type": "span-marker",
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"span_marker_version": "1.0.0.dev",
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"torch_dtype": "float32",
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"transformers_version": "4.27.2",
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"vocab_size": 30524
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 17571375
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version https://git-lfs.github.com/spec/v1
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oid sha256:7fad7460497ee6440ffe865221630a4d1b576a9cf192ed8ef9785a500e20ea0d
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size 17571375
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tokenizer_config.json
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length":
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 1000000000000000019884624838656,
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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