Instructions to use davanstrien/dataset-rows-task-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/dataset-rows-task-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/dataset-rows-task-classifier", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/dataset-rows-task-classifier", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("davanstrien/dataset-rows-task-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "EncoderForSequenceClassification" | |
| ], | |
| "auto_map": { | |
| "AutoModel": "modeling_lfm2_bidirectional.Lfm2BidirectionalModel", | |
| "AutoModelForMaskedLM": "modeling_lfm2_bidirectional.Lfm2BidirectionalForMaskedLM", | |
| "AutoModelForSequenceClassification": "modeling_encoder_seq_cls.EncoderForSequenceClassification" | |
| }, | |
| "block_auto_adjust_ff_dim": true, | |
| "block_dim": 1024, | |
| "block_ffn_dim_multiplier": 1.0, | |
| "block_mlp_init_scale": 1.0, | |
| "block_multiple_of": 256, | |
| "block_norm_eps": 1e-05, | |
| "block_out_init_scale": 1.0, | |
| "block_use_swiglu": true, | |
| "block_use_xavier_init": true, | |
| "bos_token_id": 1, | |
| "classifier_thresholds": [ | |
| 0.35, | |
| 0.15, | |
| 0.2, | |
| 0.15, | |
| 0.15, | |
| 0.4, | |
| 0.1, | |
| 0.15, | |
| 0.2, | |
| 0.1, | |
| 0.2, | |
| 0.3, | |
| 0.2, | |
| 0.35, | |
| 0.3, | |
| 0.25, | |
| 0.55, | |
| 0.5, | |
| 0.3, | |
| 0.05, | |
| 0.4, | |
| 0.25, | |
| 0.4, | |
| 0.3, | |
| 0.2, | |
| 0.35, | |
| 0.25, | |
| 0.45, | |
| 0.3, | |
| 0.25, | |
| 0.25, | |
| 0.1, | |
| 0.1, | |
| 0.2, | |
| 0.15 | |
| ], | |
| "conv_L_cache": 3, | |
| "conv_bias": false, | |
| "conv_dim": 1024, | |
| "conv_dim_out": 1024, | |
| "conv_use_xavier_init": true, | |
| "dtype": "float32", | |
| "eos_token_id": 7, | |
| "full_attn_idxs": null, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "audio-classification", | |
| "1": "audio-to-audio", | |
| "10": "image-to-image", | |
| "11": "image-to-text", | |
| "12": "multiple-choice", | |
| "13": "object-detection", | |
| "14": "question-answering", | |
| "15": "reinforcement-learning", | |
| "16": "robotics", | |
| "17": "sentence-similarity", | |
| "18": "summarization", | |
| "19": "table-question-answering", | |
| "2": "automatic-speech-recognition", | |
| "20": "tabular-classification", | |
| "21": "tabular-regression", | |
| "22": "text-classification", | |
| "23": "text-generation", | |
| "24": "text-retrieval", | |
| "25": "text-to-image", | |
| "26": "text-to-speech", | |
| "27": "text-to-video", | |
| "28": "time-series-forecasting", | |
| "29": "token-classification", | |
| "3": "feature-extraction", | |
| "30": "translation", | |
| "31": "video-classification", | |
| "32": "video-text-to-text", | |
| "33": "visual-question-answering", | |
| "34": "zero-shot-classification", | |
| "4": "fill-mask", | |
| "5": "image-classification", | |
| "6": "image-feature-extraction", | |
| "7": "image-segmentation", | |
| "8": "image-text-to-text", | |
| "9": "image-to-3d" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6656, | |
| "label2id": { | |
| "audio-classification": 0, | |
| "audio-to-audio": 1, | |
| "automatic-speech-recognition": 2, | |
| "feature-extraction": 3, | |
| "fill-mask": 4, | |
| "image-classification": 5, | |
| "image-feature-extraction": 6, | |
| "image-segmentation": 7, | |
| "image-text-to-text": 8, | |
| "image-to-3d": 9, | |
| "image-to-image": 10, | |
| "image-to-text": 11, | |
| "multiple-choice": 12, | |
| "object-detection": 13, | |
| "question-answering": 14, | |
| "reinforcement-learning": 15, | |
| "robotics": 16, | |
| "sentence-similarity": 17, | |
| "summarization": 18, | |
| "table-question-answering": 19, | |
| "tabular-classification": 20, | |
| "tabular-regression": 21, | |
| "text-classification": 22, | |
| "text-generation": 23, | |
| "text-retrieval": 24, | |
| "text-to-image": 25, | |
| "text-to-speech": 26, | |
| "text-to-video": 27, | |
| "time-series-forecasting": 28, | |
| "token-classification": 29, | |
| "translation": 30, | |
| "video-classification": 31, | |
| "video-text-to-text": 32, | |
| "visual-question-answering": 33, | |
| "zero-shot-classification": 34 | |
| }, | |
| "layer_types": [ | |
| "conv", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "full_attention", | |
| "conv" | |
| ], | |
| "max_position_embeddings": 128000, | |
| "model_type": "lfm2", | |
| "norm_eps": 1e-05, | |
| "num_attention_heads": 16, | |
| "num_heads": 16, | |
| "num_hidden_layers": 16, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 0, | |
| "problem_type": "multi_label_classification", | |
| "rope_parameters": { | |
| "rope_theta": 1000000.0, | |
| "rope_type": "default" | |
| }, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.14.1", | |
| "use_cache": false, | |
| "use_pos_enc": true, | |
| "vocab_size": 65536 | |
| } |