Instructions to use EasonShen/Lab8_szy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EasonShen/Lab8_szy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EasonShen/Lab8_szy")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EasonShen/Lab8_szy") model = AutoModelForTokenClassification.from_pretrained("EasonShen/Lab8_szy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +50 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
config.json
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{
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"activation_dropout": 0.0,
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2ForTokenClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"attn_pdrop": 0.1,
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"bos_token_id": 0,
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"embd_pdrop": 0.1,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"layer_norm_eps": 1e-12,
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"layer_norm_epsilon": 1e-05,
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"layerdrop": 0.0,
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"model_type": "gpt2",
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"n_embd": 1024,
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"n_head": 16,
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"n_inner": null,
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"n_layer": 24,
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"n_positions": 1024,
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"pad_token_id": 1,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"scale_embedding": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.38.2",
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"use_cache": true,
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"vocab_size": 42384
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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 sha256:81edf03e4864b2482782876916075d78706c35b7b6fd818d26effa4d0f2ffdb7
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size 1387087524
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:82e98b87c0b5ab432a7d650f5ecbd94e4109afd688e0964f6f5e8ab2bf3b2345
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size 4856
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