Instructions to use Arthur-Tsai/xlnetFv4_ftis_noPretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arthur-Tsai/xlnetFv4_ftis_noPretrain with Transformers:
# Load model directly from transformers import XLNetCLS model = XLNetCLS.from_pretrained("Arthur-Tsai/xlnetFv4_ftis_noPretrain", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files
config.json
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{
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"architectures": [
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"XLNetCLS"
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],
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"dropout": 0.2,
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"max_doc_len": 4500,
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"max_sent_len": 256,
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"model_type": "xlnet-cls",
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"n_head": 8,
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"num_aux_smlm_labels": 0,
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"num_aux_spo_labels": 0,
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"num_aux_tssp_labels": 0,
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"num_layers": 2,
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"num_main_labels": 36,
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"torch_dtype": "float32",
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"transformers_version": "4.46.0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b4df3b71532a021a7933869955c8ae148aa88faf3f50958c4a722fee20103718
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size 159849712
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runs/0-sample_rate=0.2/events.out.tfevents.1739000975.yara2.1265398.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:1b203b8b9e6eac0c6cfc3e40da67ec6ec216f799711265fa81225fa25d931a85
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size 9271
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:816f085268c6ad2d3e8c1b9f158feb9026718d9343c6e19da2d2f19b45cc2ace
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size 5240
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