Instructions to use foundkim/topic_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use foundkim/topic_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="foundkim/topic_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("foundkim/topic_classifier") model = AutoModelForSequenceClassification.from_pretrained("foundkim/topic_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from foundkim/topic_classifier: direct link, hf CLI and curl.
- Browser
- Download file 962 Bytes
-
https://huggingface.co/foundkim/topic_classifier/resolve/main/config.json
- Command line
-
hf download hf://foundkim/topic_classifier/config.json
-
curl -L -o config.json https://huggingface.co/foundkim/topic_classifier/resolve/main/config.json
962 Bytes
| { | |
| "_name_or_path": "bert-base-cased", | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "chiffres", | |
| "1": "mesures", | |
| "2": "opinions", | |
| "3": "sympt么mes", | |
| "4": "divers" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "chiffres": 0, | |
| "mesures": 1, | |
| "opinions": 2, | |
| "sympt么mes": 3, | |
| "divers": 4 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.10.2", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 28996 | |
| } |