Instructions to use WesScivetti/GPT-BERT_Random_Seed2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WesScivetti/GPT-BERT_Random_Seed2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="WesScivetti/GPT-BERT_Random_Seed2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("WesScivetti/GPT-BERT_Random_Seed2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from WesScivetti/GPT-BERT_Random_Seed2: direct link, hf CLI and curl.
- Browser
- Download file 230 Bytes
-
https://huggingface.co/WesScivetti/GPT-BERT_Random_Seed2/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://WesScivetti/GPT-BERT_Random_Seed2/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/WesScivetti/GPT-BERT_Random_Seed2/resolve/main/tokenizer_config.json
230 Bytes
| { | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "bos_token": "<s>", | |
| "eos_token": "</s>", | |
| "unk_token": "<unk>", | |
| "sep_token": "</s>", | |
| "pad_token": "<pad>", | |
| "cls_token": "<s>", | |
| "mask_token": "<mask>" | |
| } |