Instructions to use MOSS550V/divination with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MOSS550V/divination with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MOSS550V/divination", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MOSS550V/divination", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "tokenization_chatglm.ChatGLMTokenizer", | |
| null | |
| ] | |
| }, | |
| "bos_token": "<sop>", | |
| "do_lower_case": false, | |
| "end_token": "</s>", | |
| "eos_token": "<eop>", | |
| "gmask_token": "[gMASK]", | |
| "mask_token": "[MASK]", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "num_image_tokens": 0, | |
| "pad_token": "<pad>", | |
| "padding_side": "left", | |
| "remove_space": false, | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "ChatGLMTokenizer", | |
| "unk_token": "<unk>" | |
| } | |