Instructions to use ashani/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashani/lora_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ashani/lora_model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use ashani/lora_model 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 ashani/lora_model 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 ashani/lora_model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ashani/lora_model to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="ashani/lora_model", max_seq_length=2048, )
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- adapter_config.json +9 -11
- adapter_model.safetensors +2 -2
adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping":
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"bias": "none",
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"corda_config": null,
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"eva_config": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha":
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"lora_bias": false,
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"lora_dropout": 0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r":
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"k_proj",
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"o_proj",
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"up_proj",
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"v_proj",
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"task_type":
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"trainable_token_indices": null,
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"use_dora": false,
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"use_rslora": false
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{
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"alpha_pattern": {},
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"auto_mapping": {
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"base_model_class": "WhisperForConditionalGeneration",
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"parent_library": "transformers.models.whisper.modeling_whisper"
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},
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"base_model_name_or_path": "unsloth/whisper-large-v3",
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"bias": "none",
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"corda_config": null,
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"eva_config": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 64,
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"lora_bias": false,
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"lora_dropout": 0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 64,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"q_proj"
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],
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"task_type": null,
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"trainable_token_indices": null,
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"use_dora": false,
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"use_rslora": false
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adapter_model.safetensors
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