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")# pip install -U transformers accelerate # 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
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Download README.md from Source82/chemDataset-model_merged: direct link, hf CLI and curl.
- Browser
- Download file 595 Bytes
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https://huggingface.co/Source82/chemDataset-model_merged/resolve/main/README.md
- Command line
-
hf download hf://Source82/chemDataset-model_merged/README.md
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curl -L -o README.md https://huggingface.co/Source82/chemDataset-model_merged/resolve/main/README.md
595 Bytes
metadata
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 and Huggingface's TRL library.
