library_name: peft
datasets:
- squad
language:
- en
tags:
- llms
- falcon-7b
- open source llms
- fine tuning llms
- QLoRA
- PEFT
- LoRA
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
🚀 Falcon-7b-chat-oasst1
Falcon-7b-chat-oasst1 is a chatbot-like model for dialogue generation. It was built by fine-tuning Falcon-7B on the OpenAssistant/oasst1 dataset. This repo only includes the LoRA 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: OpenAssistant/oasst1 (License: Apache 2.0)
- License(s): Apache 2.0 inherited from "Base Model" and "Dataset"
Model Details
The model was fine-tuned in 8-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 6.25 hours and was executed on a workstation with a single A100-SXM NVIDIA GPU with 37 GB of available memory. See attached Colab Notebook for the code and hyperparams used to train the model.
Model Date
May 30, 2023
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