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
-
https://huggingface.co/m7alek/lora_model/resolve/main/README.md
- Command line
-
hf download hf://m7alek/lora_model/README.md
-
curl -L -o README.md https://huggingface.co/m7alek/lora_model/resolve/main/README.md
313 Bytes
metadata
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