Instructions to use doraking/finpath-autoscientist-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use doraking/finpath-autoscientist-model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/gpt-oss-20b-bf16") model = PeftModel.from_pretrained(base_model, "doraking/finpath-autoscientist-model") - Notebooks
- Google Colab
- Kaggle
File size: 772 Bytes
908c71f | 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 | {
"model": "openai/gpt-oss-20b",
"challenge": "Adaption AutoScientist Challenge Part 2",
"project": "finpath-autoscientist",
"category": "personal-finance",
"training_method": "sft",
"training_type": "lora",
"data_format": "instruction",
"adapted_dataset_rows": 28000,
"hyperparams": {
"base_model_size": "20B",
"n_epochs": 5,
"batch_size": "max",
"learning_rate": 0.0001,
"lora": true,
"lora_r": 64,
"lora_alpha": 128,
"lora_dropout": 0,
"lora_trainable_modules": "q_proj,k_proj,v_proj,o_proj",
"lr_scheduler_type": "cosine",
"min_lr_ratio": 0.1,
"scheduler_num_cycles": 0.5,
"warmup_ratio": 0.03,
"max_grad_norm": 1,
"weight_decay": 0.01,
"n_evals": 5,
"train_on_inputs": false
}
}
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