Instructions to use tanganke/gpt2_rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanganke/gpt2_rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tanganke/gpt2_rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tanganke/gpt2_rte") model = AutoModelForSequenceClassification.from_pretrained("tanganke/gpt2_rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from tanganke/gpt2_rte: direct link, hf CLI and curl.
- Browser
- Download file 524 Bytes
-
https://huggingface.co/tanganke/gpt2_rte/resolve/dcd99d391850e5581b458620ce8a9c4e02ff6fec/tokenizer_config.json
- Command line
-
hf download hf://tanganke/gpt2_rte@dcd99d391850e5581b458620ce8a9c4e02ff6fec/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/tanganke/gpt2_rte/resolve/dcd99d391850e5581b458620ce8a9c4e02ff6fec/tokenizer_config.json
524 Bytes
| { | |
| "add_bos_token": false, | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
| "50256": { | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "model_max_length": 512, | |
| "pad_token": "<|endoftext|>", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |