Text Classification
Transformers
Safetensors
xlm-roberta
spam-detection
content-filtering
security
nlp
efficiency
text-embeddings-inference
Instructions to use NickupAI/Nickup-Swallow-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NickupAI/Nickup-Swallow-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NickupAI/Nickup-Swallow-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NickupAI/Nickup-Swallow-v2") model = AutoModelForSequenceClassification.from_pretrained("NickupAI/Nickup-Swallow-v2") - Notebooks
- Google Colab
- Kaggle
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<s>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "1": { | |
| "content": "<pad>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": "</s>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "3": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "250001": { | |
| "content": "<mask>", | |
| "lstrip": true, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": false, | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "extra_special_tokens": {}, | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "XLMRobertaTokenizerFast", | |
| "unk_token": "<unk>" | |
| } | |