Instructions to use Xenova/tiny-random-RoFormerForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/tiny-random-RoFormerForSequenceClassification with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'Xenova/tiny-random-RoFormerForSequenceClassification');
Download config.json from Xenova/tiny-random-RoFormerForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 652 Bytes
-
https://huggingface.co/Xenova/tiny-random-RoFormerForSequenceClassification/resolve/fbc9b94cf370b400a8e85bbb7449565140db153f/config.json
- Command line
-
hf download hf://Xenova/tiny-random-RoFormerForSequenceClassification@fbc9b94cf370b400a8e85bbb7449565140db153f/config.json
-
curl -L -o config.json https://huggingface.co/Xenova/tiny-random-RoFormerForSequenceClassification/resolve/fbc9b94cf370b400a8e85bbb7449565140db153f/config.json
652 Bytes
| { | |
| "_name_or_path": "hf-tiny-model-private/tiny-random-RoFormerForSequenceClassification", | |
| "architectures": [ | |
| "RoFormerForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "embedding_size": 32, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 32, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 37, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "roformer", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 5, | |
| "pad_token_id": 0, | |
| "rotary_value": false, | |
| "transformers_version": "4.37.0.dev0", | |
| "type_vocab_size": 16, | |
| "use_cache": true, | |
| "vocab_size": 50000 | |
| } | |