Instructions to use saadlohani/polystring-lid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saadlohani/polystring-lid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="saadlohani/polystring-lid")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("saadlohani/polystring-lid") model = AutoModelForTokenClassification.from_pretrained("saadlohani/polystring-lid", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "XLMRobertaForTokenClassification" | |
| ], | |
| "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": "en", | |
| "1": "es", | |
| "2": "fr", | |
| "3": "de", | |
| "4": "pt", | |
| "5": "it", | |
| "6": "nl", | |
| "7": "pl", | |
| "8": "ro", | |
| "9": "sv", | |
| "10": "no", | |
| "11": "da", | |
| "12": "fi", | |
| "13": "cs", | |
| "14": "sk", | |
| "15": "hu", | |
| "16": "hr", | |
| "17": "ca", | |
| "18": "tr", | |
| "19": "id", | |
| "20": "ms", | |
| "21": "tl", | |
| "22": "sw", | |
| "23": "vi", | |
| "24": "af", | |
| "25": "ar", | |
| "26": "fa", | |
| "27": "ur", | |
| "28": "hi", | |
| "29": "ur-Latn", | |
| "30": "bn", | |
| "31": "ta", | |
| "32": "te", | |
| "33": "ml", | |
| "34": "mr", | |
| "35": "gu", | |
| "36": "kn", | |
| "37": "pa", | |
| "38": "ne", | |
| "39": "si", | |
| "40": "ru", | |
| "41": "uk", | |
| "42": "bg", | |
| "43": "sr", | |
| "44": "zh", | |
| "45": "ja", | |
| "46": "ko", | |
| "47": "NE", | |
| "48": "OTHER", | |
| "49": "MIX", | |
| "50": "AMB" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "AMB": 50, | |
| "MIX": 49, | |
| "NE": 47, | |
| "OTHER": 48, | |
| "af": 24, | |
| "ar": 25, | |
| "bg": 42, | |
| "bn": 30, | |
| "ca": 17, | |
| "cs": 13, | |
| "da": 11, | |
| "de": 3, | |
| "en": 0, | |
| "es": 1, | |
| "fa": 26, | |
| "fi": 12, | |
| "fr": 2, | |
| "gu": 35, | |
| "hi": 28, | |
| "hr": 16, | |
| "hu": 15, | |
| "id": 19, | |
| "it": 5, | |
| "ja": 45, | |
| "kn": 36, | |
| "ko": 46, | |
| "ml": 33, | |
| "mr": 34, | |
| "ms": 20, | |
| "ne": 38, | |
| "nl": 6, | |
| "no": 10, | |
| "pa": 37, | |
| "pl": 7, | |
| "pt": 4, | |
| "ro": 8, | |
| "ru": 40, | |
| "si": 39, | |
| "sk": 14, | |
| "sr": 43, | |
| "sv": 9, | |
| "sw": 22, | |
| "ta": 31, | |
| "te": 32, | |
| "tl": 21, | |
| "tr": 18, | |
| "uk": 41, | |
| "ur": 27, | |
| "ur-Latn": 29, | |
| "vi": 23, | |
| "zh": 44 | |
| }, | |
| "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", | |
| "transformers_version": "4.57.6", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 250002 | |
| } | |