Instructions to use zai-org/chatglm-6b-int4-qe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/chatglm-6b-int4-qe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="zai-org/chatglm-6b-int4-qe", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zai-org/chatglm-6b-int4-qe", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zai-org/chatglm-6b-int4-qe: direct link, hf CLI and curl.
- Browser
- Download file 3.36 GB
-
https://huggingface.co/zai-org/chatglm-6b-int4-qe/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zai-org/chatglm-6b-int4-qe/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zai-org/chatglm-6b-int4-qe/resolve/main/pytorch_model.bin
3.36 GB
- Xet hash:
- 43f33eaad2cf87b0c80e2e5bc0ac110a49445bc20260af5028ae670ad06fdbe8
- Size of remote file:
- 3.36 GB
- SHA256:
- 80d4ec14a9cc30ec566a54463bfdc6ce5dd5a5b63c6d51f5186cf44bf8e2eb4e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.