Instructions to use Taykhoom/gLM-650M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/gLM-650M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/gLM-650M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/gLM-650M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Taykhoom/gLM-650M: direct link, hf CLI and curl.
- Browser
- Download file 207 Bytes
-
https://huggingface.co/Taykhoom/gLM-650M/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Taykhoom/gLM-650M/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Taykhoom/gLM-650M/resolve/main/special_tokens_map.json
207 Bytes
| { | |
| "cls_token": "<cls>", | |
| "eos_token": "<eos>", | |
| "mask_token": "<mask>", | |
| "pad_token": "<pad>", | |
| "sep_token": "<sep>", | |
| "unk_token": "<unk>", | |
| "additional_special_tokens": [ | |
| "<+>", | |
| "<->" | |
| ] | |
| } |