Update README.md
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README.md
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@@ -139,102 +139,6 @@ The model was fine-tuned as a regular BERT-based model for NER task using Huggin
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>>> classifier(text)
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model.safetensors: 0%| | 0.00/496M [00:00<?, ?B/s]CommitInfo(commit_url='https://huggingface.co/guishe/nuner-v1_fewnerd_fine_super/commit/4313d72902c1e518c0f84c7884b8327c59b671d6', commit_message='Upload RobertaForTokenClassification', commit_description='', oid='4313d72902c1e518c0f84c7884b8327c59b671d6', pr_url=None, pr_revision=None, pr_num=None)
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Token is valid (permission: write).
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[1m[31mCannot authenticate through git-credential as no helper is defined on your machine.
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You might have to re-authenticate when pushing to the Hugging Face Hub.
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Run the following command in your terminal in case you want to set the 'store' credential helper as default.
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git config --global credential.helper store
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Read https://git-scm.com/book/en/v2/Git-Tools-Credential-Storage for more details.[0m
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Token has not been saved to git credential helper.
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Your token has been saved to /root/.cache/huggingface/token
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Login successful
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CommitInfo(commit_url='https://huggingface.co/guishe/nuner-v2_fewnerd_fine_super/commit/904729b29bb8cbaf4aa1e1a7e8ec00ada35a6e48', commit_message='Upload training_args.bin with huggingface_hub', commit_description='', oid='904729b29bb8cbaf4aa1e1a7e8ec00ada35a6e48', pr_url=None, pr_revision=None, pr_num=None)
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DatasetDict({
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train: Dataset({
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features: ['id', 'tokens', 'ner_tags', 'fine_ner_tags'],
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num_rows: 131767
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})
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validation: Dataset({
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features: ['id', 'tokens', 'ner_tags', 'fine_ner_tags'],
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num_rows: 18824
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})
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test: Dataset({
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features: ['id', 'tokens', 'ner_tags', 'fine_ner_tags'],
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num_rows: 37648
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})
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})
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{'id': '0',
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'tokens': ['Paul', 'International', 'airport', '.'],
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'ner_tags': [0, 0, 0, 0]}
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['O',
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'art-broadcastprogram',
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'art-film',
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'art-music',
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'art-other',
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'art-painting',
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'art-writtenart',
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'building-airport',
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'building-hospital',
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'building-hotel',
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'building-library',
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'building-other',
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'building-restaurant',
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'building-sportsfacility',
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'building-theater',
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'event-attack/battle/war/militaryconflict',
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'event-disaster',
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'event-election',
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'event-other',
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'event-protest',
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'event-sportsevent',
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'location-GPE',
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'location-bodiesofwater',
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'location-island',
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'location-mountain',
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'location-other',
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'location-park',
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'location-road/railway/highway/transit',
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'organization-company',
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'organization-education',
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'organization-government/governmentagency',
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'organization-media/newspaper',
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'organization-other',
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'organization-politicalparty',
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'organization-religion',
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'organization-showorganization',
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'organization-sportsleague',
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'organization-sportsteam',
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'other-astronomything',
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'other-award',
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'other-biologything',
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'other-chemicalthing',
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'other-currency',
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'other-disease',
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'other-educationaldegree',
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'other-god',
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'other-language',
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'other-law',
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'other-livingthing',
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'other-medical',
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'person-actor',
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'person-artist/author',
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'person-athlete',
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'person-director',
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'person-other',
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...
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'product-other',
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'product-ship',
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'product-software',
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'product-train',
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'product-weapon']
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Output is truncated. View as a scrollable element or open in a text editor. Adjust cell output settings...
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Could not render content for 'application/vnd.jupyter.widget-view+json'
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{"model_id":"736c5e1a1648445290af4bfe84dd9a2d","version_major":2,"version_minor":0}
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['<s>', 'ĠPaul', 'ĠInternational', 'Ġairport', 'Ġ.', '</s>']
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['O', 'O', 'O', 'O']
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Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at numind/NuNER-v1.0 and are newly initialized: ['classifier.bias', 'classifier.weight']
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You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
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[{'entity_group': 'location_GPE',
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'score': 0.96503985,
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'word': ' Washington',
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)
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>>> classifier(text)
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[{'entity_group': 'location_GPE',
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'score': 0.96503985,
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'word': ' Washington',
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