Text Classification
Transformers
PyTorch
multilingual
English
distilbert
sentiment-analysis
testing
unit tests
Instructions to use dhpollack/distilbert-dummy-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhpollack/distilbert-dummy-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dhpollack/distilbert-dummy-sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dhpollack/distilbert-dummy-sentiment") model = AutoModelForSequenceClassification.from_pretrained("dhpollack/distilbert-dummy-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from dhpollack/distilbert-dummy-sentiment: direct link, hf CLI and curl.
- Browser
- Download file 577 Bytes
-
https://huggingface.co/dhpollack/distilbert-dummy-sentiment/resolve/refs%2Fpr%2F1/config.json
- Command line
-
hf download hf://dhpollack/distilbert-dummy-sentiment@refs/pr/1/config.json
-
curl -L -o config.json https://huggingface.co/dhpollack/distilbert-dummy-sentiment/resolve/refs%2Fpr%2F1/config.json
577 Bytes
| { | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForSequenceClassification" | |
| ], | |
| "attention_dropout": 0.1, | |
| "dim": 1, | |
| "dropout": 0.1, | |
| "hidden_dim": 4, | |
| "id2label": { | |
| "0": "negative", | |
| "1": "positive" | |
| }, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "negative": 0, | |
| "positive": 1 | |
| }, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 1, | |
| "n_layers": 1, | |
| "pad_token_id": 0, | |
| "qa_dropout": 0.1, | |
| "seq_classif_dropout": 0.2, | |
| "sinusoidal_pos_embds": false, | |
| "transformers_version": "4.4.2", | |
| "vocab_size": 5 | |
| } | |