Instructions to use Source82/chemDataset-model_merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Source82/chemDataset-model_merged with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Source82/chemDataset-model_merged")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Source82/chemDataset-model_merged") model = AutoModel.from_pretrained("Source82/chemDataset-model_merged", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
| base_model: unsloth/Qwen2.5-VL-3B-Instruct | |
| tags: | |
| - text-generation-inference | |
| - transformers | |
| - unsloth | |
| - qwen2_5_vl | |
| license: apache-2.0 | |
| language: | |
| - en | |
| # Uploaded finetuned model | |
| - **Developed by:** Source82 | |
| - **License:** apache-2.0 | |
| - **Finetuned from model :** unsloth/Qwen2.5-VL-3B-Instruct | |
| This qwen2_5_vl model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. | |
| [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) | |