Text Classification
Transformers
Joblib
Safetensors
multilingual
binary-classification
amis
agriculture
Instructions to use faodl/agri-utilization-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faodl/agri-utilization-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="faodl/agri-utilization-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("faodl/agri-utilization-classifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "XLMRobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "NOT_RELEVANT", | |
| "1": "RELEVANT" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "NOT_RELEVANT": 0, | |
| "RELEVANT": 1 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "threshold": 0.8530579209327698, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.11.0", | |
| "type_vocab_size": 1, | |
| "use_cache": false, | |
| "validation_threshold_report": { | |
| "f1": 0.8176100628930818, | |
| "precision": 0.8125, | |
| "recall": 0.8227848101265823, | |
| "threshold": 0.8530579209327698 | |
| }, | |
| "vocab_size": 250002 | |
| } | |