Document Question Answering
Transformers
Safetensors
chatglm
feature-extraction
text-generation-inference
custom_code
4-bit precision
bitsandbytes
Instructions to use nikravan/glm-4vq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikravan/glm-4vq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="nikravan/glm-4vq", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nikravan/glm-4vq", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Sample example does not work.
#8 opened about 1 year ago
by
hitoruna
Some modules are dispatched on the CPU or the disk
#7 opened over 1 year ago
by
chamy
dependency compatibility
1
#5 opened over 1 year ago
by
mdicio
got an unexpected keyword argument 'standardize_cache_format'
👍 1
#4 opened over 1 year ago
by
CCChen
Pipeline not working
#3 opened almost 2 years ago
by
lucabot
May I ask how the quantification is achieved?
1
#2 opened almost 2 years ago
by
alexwww94
ValueError: too many values to unpack (expected 2)
1
#1 opened almost 2 years ago
by
vivasvan100