Instructions to use hf-internal-testing/tiny-random-GPTNeoXJapaneseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoXJapaneseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-GPTNeoXJapaneseModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoXJapaneseModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-GPTNeoXJapaneseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<|startoftext|>", | |
| "do_clean_text": false, | |
| "eos_token": "<|endoftext|>", | |
| "model_max_length": 512, | |
| "name_or_path": "abeja/gpt-neox-japanese-2.7b", | |
| "pad_token": "<|endoftext|>", | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "GPTNeoXJapaneseTokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |