Feature Extraction
Transformers.js
ONNX
English
bert
decidekit
system-one
text-classification
zero-shot-classification
calibration
on-device
Instructions to use debuffjp/decide-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use debuffjp/decide-small with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'debuffjp/decide-small');
Download config.json from debuffjp/decide-small: direct link, hf CLI and curl.
- Browser
- Download file 683 Bytes
-
https://huggingface.co/debuffjp/decide-small/resolve/main/config.json
- Command line
-
hf download hf://debuffjp/decide-small/config.json
-
curl -L -o config.json https://huggingface.co/debuffjp/decide-small/resolve/main/config.json
683 Bytes
| { | |
| "_name_or_path": "BAAI/bge-small-en-v1.5", | |
| "architectures": [ | |
| "BertModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 384, | |
| "id2label": { | |
| "0": "LABEL_0" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "label2id": { | |
| "LABEL_0": 0 | |
| }, | |
| "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", | |
| "transformers_version": "4.34.0.dev0", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 30522 | |
| } | |