Instructions to use mahmoudOmar03/Mahmoud with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahmoudOmar03/Mahmoud with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mahmoudOmar03/Mahmoud", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use mahmoudOmar03/Mahmoud with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mahmoudOmar03/Mahmoud to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mahmoudOmar03/Mahmoud to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mahmoudOmar03/Mahmoud to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="mahmoudOmar03/Mahmoud", max_seq_length=2048, )
Create config.json
Browse files- config.json +14 -0
config.json
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{
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"model_type": "llama",
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"hidden_size": 512,
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"num_hidden_layers": 12,
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"num_attention_heads": 8,
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"intermediate_size": 2048,
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"hidden_act": "gelu",
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"initializer_range": 0.02,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"vocab_size": 32000,
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"dropout": 0.1,
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"attention_probs_dropout_prob": 0.1
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}
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