Instructions to use zai-org/glm-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/glm-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="zai-org/glm-roberta-large", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("zai-org/glm-roberta-large", trust_remote_code=True) model = AutoModel.from_pretrained("zai-org/glm-roberta-large", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zai-org/glm-roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/zai-org/glm-roberta-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zai-org/glm-roberta-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zai-org/glm-roberta-large/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 57eba6859bcb56e54073ebbd801c692a13536fa0c2586ef47287b8c86b406614
- Size of remote file:
- 1.42 GB
- SHA256:
- 65469e3145ee0bb7db36e1c3adca8ea4c3a9a97bdca2b3362ddd3b2d948fc47d
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