Instructions to use kejian/cond-0-misaligned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/cond-0-misaligned with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/cond-0-misaligned") model = AutoModel.from_pretrained("kejian/cond-0-misaligned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-30000/tokenizer_config.json from kejian/cond-0-misaligned: direct link, hf CLI and curl.
- Browser
- Download file 278 Bytes
-
https://huggingface.co/kejian/cond-0-misaligned/resolve/main/checkpoint-30000/tokenizer_config.json
- Command line
-
hf download hf://kejian/cond-0-misaligned/checkpoint-30000/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/kejian/cond-0-misaligned/resolve/main/checkpoint-30000/tokenizer_config.json
278 Bytes
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<|endoftext|>", | |
| "eos_token": "<|endoftext|>", | |
| "model_max_length": 1024, | |
| "name_or_path": "codeparrot/codeparrot-small", | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |