Text Classification
Transformers
PyTorch
Safetensors
Spanish
electra
restaurant
classification
reviews
Instructions to use mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "mrm8488/electricidad-small-discriminator", | |
| "architectures": [ | |
| "ElectraForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "embedding_size": 128, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 256, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1024, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "electra", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "summary_activation": "gelu", | |
| "summary_last_dropout": 0.1, | |
| "summary_type": "first", | |
| "summary_use_proj": true, | |
| "transformers_version": "4.7.0.dev0", | |
| "type_vocab_size": 2, | |
| "vocab_size": 31002 | |
| } | |