Instructions to use bha6kar/finance-lora-deepseek-r1-1.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use bha6kar/finance-lora-deepseek-r1-1.5b with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download bha6kar/finance-lora-deepseek-r1-1.5b --local-dir finance-lora-deepseek-r1-1.5b
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Upload folder using huggingface_hub
Browse files- 0000120_adapters.safetensors +3 -0
- adapter_config.json +41 -0
- adapters.safetensors +3 -0
- lora_config.yaml +20 -0
0000120_adapters.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:12ad72c3fcb9e363947f657aae9d73e4dfbad7c0af79e80497bbdffbe1985f15
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size 10563230
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adapter_config.json
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{
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"adapter_path": "/Users/onyx/crasher/slm-training/adapters/deepseek-r1-1.5b/seed42",
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"batch_size": 4,
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"clear_cache_threshold": 0,
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"config": "/Users/onyx/crasher/slm-training/adapters/deepseek-r1-1.5b/seed42/lora_config.yaml",
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"data": "/Users/onyx/crasher/slm-training/data",
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"fine_tune_type": "lora",
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"grad_accumulation_steps": 1,
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"grad_checkpoint": false,
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"iters": 120,
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"learning_rate": 0.0001,
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"lora_parameters": {
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"rank": 8,
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"scale": 20.0,
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"dropout": 0.0
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},
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"lr_schedule": null,
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"mask_prompt": false,
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"max_seq_length": 1024,
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"model": "mlx-community/DeepSeek-R1-Distill-Qwen-1.5B-4bit",
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"num_layers": 8,
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"optimizer": "adam",
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"optimizer_config": {
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"adam": {},
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"adamw": {},
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"muon": {},
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"sgd": {},
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"adafactor": {}
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},
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"project_name": null,
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"report_to": null,
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"resume_adapter_file": null,
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"save_every": 120,
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"seed": 42,
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"steps_per_eval": 40,
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"steps_per_report": 20,
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"test": false,
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"test_batches": 500,
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"train": true,
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"val_batches": 8
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}
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adapters.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:12ad72c3fcb9e363947f657aae9d73e4dfbad7c0af79e80497bbdffbe1985f15
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size 10563230
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lora_config.yaml
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model: mlx-community/DeepSeek-R1-Distill-Qwen-1.5B-4bit
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train: true
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data: /Users/onyx/crasher/slm-training/data
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seed: 42
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fine_tune_type: lora
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num_layers: 8
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batch_size: 4
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iters: 120
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learning_rate: 0.0001
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max_seq_length: 1024
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steps_per_report: 20
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steps_per_eval: 40
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val_batches: 8
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save_every: 120
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grad_checkpoint: false
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adapter_path: /Users/onyx/crasher/slm-training/adapters/deepseek-r1-1.5b/seed42
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lora_parameters:
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rank: 8
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scale: 20.0
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dropout: 0.0
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