Instructions to use Muthrid/artifact-series-83e55ac0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Muthrid/artifact-series-83e55ac0 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Muthrid/artifact-series-83e55ac0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Artifact Series
This repository contains a collection of research model checkpoint artifacts. Opaque directory identifiers are used as stable artifact labels.
artifacts/a01throughartifacts/a05use standard Transformers checkpoint layouts.artifacts/a06/s01throughartifacts/a06/s03are distributed model-state snapshots.- Optimizer state, trainer state, logs, metrics, and training-data files are not included.
No benchmark or fitness claims are made. Review each artifact's configuration before use.
PyTorch .pt files should only be loaded in a trusted environment because deserialization may execute code.
The upstream base model is
Qwen/Qwen2.5-Coder-32B-Instruct,
which is published under Apache-2.0. The repository metadata retains license: other
for these derived artifacts; users are responsible for confirming that their intended use
and redistribution comply with all applicable rights and obligations.
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Model tree for Muthrid/artifact-series-83e55ac0
Base model
Qwen/Qwen2.5-32B Finetuned
Qwen/Qwen2.5-Coder-32B Finetuned
Qwen/Qwen2.5-Coder-32B-Instruct