Instructions to use zai-org/WebGLM-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/WebGLM-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="zai-org/WebGLM-2B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("zai-org/WebGLM-2B", trust_remote_code=True) model = AutoModel.from_pretrained("zai-org/WebGLM-2B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 465 Bytes
cffa6bd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"name_or_path": "THUDM/glm-2b",
"eos_token": "<|endoftext|>",
"pad_token": "<|endoftext|>",
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"unk_token": "[UNK]",
"additional_special_tokens": ["<|startofpiece|>", "<|endofpiece|>", "[gMASK]", "[sMASK]"],
"add_prefix_space": false,
"tokenizer_class": "GLMGPT2Tokenizer",
"use_fast": false,
"auto_map": {
"AutoTokenizer": [
"tokenization_glm.GLMGPT2Tokenizer",
null
]
}
}
|