Instructions to use EasthShin/Android_Ios_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EasthShin/Android_Ios_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EasthShin/Android_Ios_Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EasthShin/Android_Ios_Classification") model = AutoModelForSequenceClassification.from_pretrained("EasthShin/Android_Ios_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from EasthShin/Android_Ios_Classification: direct link, hf CLI and curl.
- Browser
- Download file 666 Bytes
-
https://huggingface.co/EasthShin/Android_Ios_Classification/resolve/refs%2Fpr%2F1/config.json
- Command line
-
hf download hf://EasthShin/Android_Ios_Classification@refs/pr/1/config.json
-
curl -L -o config.json https://huggingface.co/EasthShin/Android_Ios_Classification/resolve/refs%2Fpr%2F1/config.json
666 Bytes
| { | |
| "_name_or_path": "bert-base-cased", | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "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", | |
| "transformers_version": "4.8.2", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 28996 | |
| } | |