Instructions to use punsaisuwan/frankenmoe-python-typescript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use punsaisuwan/frankenmoe-python-typescript with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir frankenmoe-python-typescript punsaisuwan/frankenmoe-python-typescript
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 1,116 Bytes
c13d0c1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | {
"adapter_path": "./adapters/expert-1-python-v2",
"batch_size": 1,
"config": "lora_config_expert1_v2.yaml",
"data": "./datasets/expert-1-python",
"fine_tune_type": "lora",
"grad_accumulation_steps": 1,
"grad_checkpoint": true,
"iters": 500,
"learning_rate": 1e-05,
"lora_parameters": {
"rank": 16,
"dropout": 0.0,
"scale": 8.0,
"keys": [
"self_attn.q_proj",
"self_attn.k_proj",
"self_attn.v_proj",
"self_attn.o_proj"
]
},
"lr_schedule": null,
"mask_prompt": false,
"max_seq_length": 2048,
"model": "./output-moe-mlx-4bit",
"num_layers": 16,
"optimizer": "adam",
"optimizer_config": {
"adam": {},
"adamw": {},
"muon": {},
"sgd": {},
"adafactor": {}
},
"project_name": null,
"report_to": null,
"resume_adapter_file": null,
"save_every": 50,
"seed": 0,
"steps_per_eval": 200,
"steps_per_report": 10,
"test": false,
"test_batches": 500,
"train": true,
"val_batches": 25
} |