T-Llama-v1.1

Model Details

Model Description

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• Developed by: Tuan Pham (FPTU HCM Student)
• Model type: Llama2-7B Decoder-only
• Finetuned from model :
  • meta-llama/Llama-2-7b
  • bkai-foundation-models/vietnamese-llama2-7b-120GB
  • yeen214/llama2_7b_merge_orcafamily.
• Bilingual support : English and Vietnamese

Model Sources

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• Repository:
  • Training: https://github.com/vTuanpham/Vietnamese_QA_System
  • Data: https://github.com/vTuanpham/Large_dataset_translator
• Paper: ...
• Demo: ...

Uses

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Prompt template

[SYSTEM_PROMPT]

 ####### Instruction:
[INPUT]

 %%%%%%% Response:
[RESPONSE]

How to Get Started with the Model

Use the code below to get started with the model.

from torch.cuda.amp import autocast
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer, pipeline

model_name = "1TuanPham/T-Llama-v1.1"
model = AutoModelForCausalLM.from_pretrained(model_name,
                                             torch_dtype=torch.bfloat16,
                                             use_cache=True,
                                             )
tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
streamer = TextStreamer(tokenizer, skip_special_tokens=True)
pipe = pipeline("text-generation", model=base_model, tokenizer=tokenizer, streamer=streamer)

with autocast():
  output_default = pipe("Phạm Nhật Vượng là ", pad_token_id=50256, max_new_tokens=128)

Training Details

Hardware Type:

• GPU: VGA NVIDIA Tesla P100 16GB
• SYSTEM RAM: 29GB

Hours used: ~42.5 Approx*

Training Data

• BactrianX
• OpenOrca_translated
• WizardLM_70k_translated
• TigerLabMathInstruct_translated_vi
• GradeSchoolMathInstruct_translated
• vilm_lima-vi
• MTEngVietnamese
• databricks_dolly15k_translated
• AlpacaCleaned_translated
• databricks_dolly15k
• OpenOrca
• GradeSchoolMathInstruct
• AlpacaCleaned
• WebglmQA

Training Procedure

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• Learning rate: 2e-5 cosine

• Optimizer: PagedLion8bit

• QLora: rank: 64 /Q: 4-bit

  • 250k examples of 70% Vietnamese 30% English for 3.37 epoch
  • 350k examples of 60% Vietnamese 40% English for 1.1 epoch

Training loss

Evaluation

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Results

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Technical Specifications

Model Architecture and Objective

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Citation

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Model Card Authors

Model Card Contact

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