Instructions to use ai-shift/sample-model-rm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai-shift/sample-model-rm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ai-shift/sample-model-rm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ai-shift/sample-model-rm") model = AutoModelForSequenceClassification.from_pretrained("ai-shift/sample-model-rm") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|padding|>", | |
| "tokenizer_class": "GPTNeoXTokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |