Instructions to use senmasa/qwen2.5-0.5b-with-no-example-1100-data-1-epochs-6000-max_length-preskripsi_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use senmasa/qwen2.5-0.5b-with-no-example-1100-data-1-epochs-6000-max_length-preskripsi_summarization with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("senmasa/qwen2.5-0.5b-with-no-example-1100-data-1-epochs-6000-max_length-preskripsi_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from senmasa/qwen2.5-0.5b-with-no-example-1100-data-1-epochs-6000-max_length-preskripsi_summarization: direct link, hf CLI and curl.
- Browser
- Download file 596 Bytes
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https://huggingface.co/senmasa/qwen2.5-0.5b-with-no-example-1100-data-1-epochs-6000-max_length-preskripsi_summarization/resolve/main/README.md
- Command line
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hf download hf://senmasa/qwen2.5-0.5b-with-no-example-1100-data-1-epochs-6000-max_length-preskripsi_summarization/README.md
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curl -L -o README.md https://huggingface.co/senmasa/qwen2.5-0.5b-with-no-example-1100-data-1-epochs-6000-max_length-preskripsi_summarization/resolve/main/README.md
596 Bytes
metadata
base_model: unsloth/Qwen2.5-0.5B-Instruct-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
license: apache-2.0
language:
- en
Uploaded model
- Developed by: senmasa
- License: apache-2.0
- Finetuned from model : unsloth/Qwen2.5-0.5B-Instruct-bnb-4bit
This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
