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
# 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")Quick Links
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 and Huggingface's TRL library.
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Model tree for Source82/chemDataset-model_merged
Base model
Qwen/Qwen2.5-VL-3B-Instruct Finetuned
unsloth/Qwen2.5-VL-3B-Instruct
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Source82/chemDataset-model_merged")