Instructions to use adityakorade/lora_code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adityakorade/lora_code with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("adityakorade/lora_code", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use adityakorade/lora_code 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 adityakorade/lora_code 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 adityakorade/lora_code to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for adityakorade/lora_code to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="adityakorade/lora_code", max_seq_length=2048, )
Upload LlamaForCausalLM
Browse files- adapter_config.json +3 -3
- generation_config.json +9 -0
adapter_config.json
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"rank_pattern": {},
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"revision": "unsloth",
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"target_modules": [
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"q_proj",
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"gate_proj",
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"up_proj",
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"down_proj",
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"o_proj",
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"v_proj",
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"k_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"rank_pattern": {},
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"revision": "unsloth",
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"target_modules": [
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"up_proj",
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"down_proj",
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"o_proj",
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"q_proj",
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"v_proj",
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"k_proj",
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"gate_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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generation_config.json
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{
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"bos_token_id": 128000,
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"do_sample": true,
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"eos_token_id": 128001,
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"max_length": 4096,
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.41.2"
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}
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