Instructions to use ipranavks/AgroGenius with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ipranavks/AgroGenius with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ipranavks/AgroGenius")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("ipranavks/AgroGenius") model = AutoModel.from_pretrained("ipranavks/AgroGenius", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
File size: 606 Bytes
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base_model: unsloth/qwen2-vl-2b-instruct-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2_vl
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** ipranavks
- **License:** apache-2.0
- **Finetuned from model :** unsloth/qwen2-vl-2b-instruct-bnb-4bit
This qwen2_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)
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