Instructions to use coagentdev/codeagent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coagentdev/codeagent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="coagentdev/codeagent")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("coagentdev/codeagent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
datasets:
- bigcode/the-stack
- bigcode/the-stack-v2
- bigcode/starcoderdata
language:
- en
metrics:
- perplexity
- code_eval
- codeparrot/apps_metric
base_model:
- zai-org/GLM-5
- deepseek-ai/DeepSeek-R1
- deepseek-ai/DeepSeek-V3.2
- deepseek-ai/DeepSeek-V3
- Qwen/Qwen3-Coder-Next
- zai-org/GLM-4.7-Flash
- mlfoundations-dev/oh-dcft-v3.1-gemini-1.5-pro
- DavidAU/Qwen3-30B-A3B-YOYO-V2-Claude-4.6-Opus-High-INSTRUCT
- moonshotai/Kimi-K2.5
new_version: google/timesfm-2.5-200m-transformers
pipeline_tag: table-question-answering
library_name: transformers
tags:
- code