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sidddd625/adaption_finance_local_devnagri_scrip
adaption_finance_local_devnagri_scrip is a text generation model from sidddd625. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as other.
A LoRA adapter fine-tuned on top of meta-llama/Llama-4-Scout-17B-16E-Instruct for finance in local Devanagari-script languages.
Downloads · 30 days
10
19% of all-time downloads
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.safetensors893 MB · 51%
From the Hugging Face model README
A LoRA adapter fine-tuned on top of meta-llama/Llama-4-Scout-17B-16E-Instruct for finance in local Devanagari-script languages.
| Metric | base | adapted |
|---|---|---|
| Win rate (your dataset) | 19 | 81 |
| Win rate (Personal Finance category) | 26 | 74 |


| Parameter | Value |
|---|---|
| lora_r | 64 |
| lora_alpha | 128 |
| lora_dropout | 0 |
| task type | CAUSAL_LM |
| trainable modules | k_proj, o_proj, q_proj, v_proj, shared_expert.gate_proj, shared_expert.up_proj, shared_expert.down_proj, feed_forward.gate_proj, feed_forward.up_proj, feed_forward.down_proj |
| Parameter | Value |
|---|---|
| n_epochs | 5 |
| n_evals | 5 |
| batch_size | max |
| learning_rate | 0.0001 |
| lr_scheduler_type | cosine |
| scheduler_num_cycles | 0.5 |
| min_lr_ratio | 0.1 |
| warmup_ratio | 0.05 |
| weight_decay | 0.02 |
| max_grad_norm | 1 |
| train_on_inputs | false |
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "meta-llama/Llama-4-Scout-17B-16E-Instruct"
adapter = "sidddd625/adaption_finance_local_devnagri_scrip"
tokenizer = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, adapter)