Instructions to use m7alek/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m7alek/lora_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("m7alek/lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from m7alek/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 313 Bytes
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https://huggingface.co/m7alek/lora_model/resolve/main/README.md
- Command line
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hf download hf://m7alek/lora_model/README.md
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curl -L -o README.md https://huggingface.co/m7alek/lora_model/resolve/main/README.md
313 Bytes
| license: mit | |
| datasets: | |
| - m7alek/external_df | |
| - m7alek/Fifth_file | |
| - m7alek/ninth_file | |
| - m7alek/eighth_file | |
| language: | |
| - ar | |
| - en | |
| metrics: | |
| - accuracy | |
| - bertscore | |
| new_version: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF | |
| library_name: transformers | |
| tags: | |
| - NLP | |
| - Text-generation | |
| base_model: | |
| - google/gemma-7b-aps-it | |