Instructions to use JohanHeinsen/Labour_advertisement_identifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JohanHeinsen/Labour_advertisement_identifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JohanHeinsen/Labour_advertisement_identifier") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - setfit
How to use JohanHeinsen/Labour_advertisement_identifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("JohanHeinsen/Labour_advertisement_identifier") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download config.json from JohanHeinsen/Labour_advertisement_identifier: direct link, hf CLI and curl.
- Browser
- Download file 583 Bytes
-
https://huggingface.co/JohanHeinsen/Labour_advertisement_identifier/resolve/a689352eca23b3abe48088dcb3fd1fc7834b2f07/config.json
- Command line
-
hf download hf://JohanHeinsen/Labour_advertisement_identifier@a689352eca23b3abe48088dcb3fd1fc7834b2f07/config.json
-
curl -L -o config.json https://huggingface.co/JohanHeinsen/Labour_advertisement_identifier/resolve/a689352eca23b3abe48088dcb3fd1fc7834b2f07/config.json
583 Bytes
| { | |
| "architectures": [ | |
| "BertModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "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", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.51.3", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 30522 | |
| } | |