Instructions to use pabagcha/alc_robertuito with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pabagcha/alc_robertuito with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pabagcha/alc_robertuito")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pabagcha/alc_robertuito") model = AutoModelForSequenceClassification.from_pretrained("pabagcha/alc_robertuito") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- .gitignore +1 -0
- config.json +42 -0
- pytorch_model.bin +3 -0
- runs/May17_18-24-56_3e8ef16d30f9/1684347901.1009881/events.out.tfevents.1684347901.3e8ef16d30f9.387.4 +3 -0
- runs/May17_18-24-56_3e8ef16d30f9/events.out.tfevents.1684347901.3e8ef16d30f9.387.3 +3 -0
- special_tokens_map.json +9 -0
- tokenizer.json +0 -0
- tokenizer_config.json +12 -0
- training_args.bin +3 -0
.gitignore
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checkpoint-*/
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config.json
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{
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"_name_or_path": "dccuchile/bert-base-spanish-wwm-cased",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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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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"3": "LABEL_3",
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"4": "LABEL_4"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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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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"LABEL_3": 3,
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"LABEL_4": 4
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.29.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 31002
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:50fb50c76efc6ec81c96798831bb010f317d77eb116ae253be970f6e80e33ace
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size 439491701
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runs/May17_18-24-56_3e8ef16d30f9/1684347901.1009881/events.out.tfevents.1684347901.3e8ef16d30f9.387.4
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version https://git-lfs.github.com/spec/v1
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oid sha256:a7046f15ff47085cd7ef2cd18792347368db80f1a565bc4564a4f3c8fa8934d5
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size 5898
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runs/May17_18-24-56_3e8ef16d30f9/events.out.tfevents.1684347901.3e8ef16d30f9.387.3
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version https://git-lfs.github.com/spec/v1
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oid sha256:24bd2629d20bbd5ba1f0b04980d69615408ddc4df249875106a9f98c266c1a25
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size 4184
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special_tokens_map.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": "<mask>",
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"unk_token": "<unk>"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": "<mask>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"tokenizer_class": "PreTrainedTokenizerFast",
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"unk_token": "<unk>"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:3fd70b3e91ecc749220a186d570798f9eec98f0863f170fbccb2306671591b81
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size 3899
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