library_name: peft
datasets:
- squad
language:
- en
tags:
- llms
- falcon-7b
- open source llms
- fine tuning llms
- QLoRA
- PEFT
- LoRA
🚀 Falcon-7b-QueAns
Falcon-7b-QueAns is a chatbot-like model for Question and Answering. It was built by fine-tuning Falcon-7B on the SQuAD dataset. This repo only includes the QLoRA adapters from fine-tuning with 🤗's peft package.
Model Summary
- Model Type: Causal decoder-only
- Language(s): English
- Base Model: [Falcon-7B] (License: [Apache 2.0])
- Dataset: SQuAD (License: [cc-by-4.0])
- License(s): Apache 2.0 inherited from "Base Model" and "Dataset"
Model Details
The model was fine-tuned in 4-bit precision using 🤗 peft adapters, transformers, and bitsandbytes. Training relied on a method called "Low Rank Adapters" (LoRA), specifically the QLoRA variant. The run took approximately 4 hours and was executed on a workstation with a single T4 NVIDIA GPU with 15 GB of available memory. See attached [Colab Notebook] used to train the model.
Model Date
July 06, 2023
Open source falcon 7b large language model fine tuned on SQuAD dataset for question and answering.
QLoRA technique used for fine tuning the model on consumer grade GPU SFTTrainer is also used.
Dataset used: SQuAD Dataset Size: 87278 Training Steps: 500
Training procedure
The following bitsandbytes quantization config was used during training:
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
The following bitsandbytes quantization config was used during training:
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16
Framework versions
PEFT 0.4.0.dev0
PEFT 0.4.0.dev0