IPSAN/tat_monocorpus_v2
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This is a LoRA adapter with rank 8 fine-tuned on Tatar language.
| Property | Value |
|---|---|
| Base Model | Mistral-7B-v0.3 |
| LoRA Rank | 8 |
| Training Data | 10,000 samples |
| Test Perplexity | 4.04 |
| Training Epochs | 2 |
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
import torch
base_model = "mistralai/Mistral-7B-v0.3"
tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(base_model, torch_dtype=torch.float16, device_map="auto")
model = PeftModel.from_pretrained(model, "TatarNLPWorld/mistral-7b-tatar-lora-r8")
prompt = "ะะธะฝะตะผ ะธัะตะผะตะผ"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0]))
Prompt: "ะะธะฝะตะผ ะธัะตะผะตะผ"
Generated: "...ะฝะตาฃ 10 ัััะปะตะบ ะฐะฝั ะฑะตะปำะฝ ัำฉะนะปำะดะตะปำั"
| Model | Perplexity |
|---|---|
| Mistral-7B r16 | 3.98 |
| Mistral-7B r8 | 4.04 |
| GPT-2 medium | 2.91 (full) |
@software{mistral_tatar_lora_r8_2026,
title = {{Mistral-7B LoRA Adapter for Tatar Language (Rank 8)}},
author = { Arabov Mullosharaf Kurbonovich},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/TatarNLPWorld/mistral-7b-tatar-lora-r8}
}
Base model
mistralai/Mistral-7B-v0.3