Downloads · 30 days
4
17% of all-time downloads
mpasila/Alpacazord-Viking-LoRA-7B
Alpacazord-Viking-LoRA-7B is a machine learning model from mpasila. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
LoRA trained with text-generation-webui in 4-bit using LumiOpen/Viking-7B as the base model for 1 epoch. Dataset used with the LoRA is mpasila/Alpacazord-V1.
Downloads · 30 days
4
17% of all-time downloads
All-time downloads
24
Public
Repo size
268 MB
Likes
0
Public
Click a slice to open those files.
.safetensors268 MB · 100%
From the Hugging Face model README
LoRA trained with text-generation-webui in 4-bit using LumiOpen/Viking-7B as the base model for 1 epoch. Dataset used with the LoRA is mpasila/Alpacazord-V1.
It uses Alpaca format like so:
{
"instruction,output": "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n%instruction%\n\n### Response:\n%output%",
"instruction,input,output": "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n%instruction%\n\n### Input:\n%input%\n\n### Response:\n%output%"
}
Using the following settings:
{
"lora_name": "Alpacazord-V4",
"always_override": false,
"q_proj_en": true,
"v_proj_en": true,
"k_proj_en": false,
"o_proj_en": false,
"gate_proj_en": false,
"down_proj_en": false,
"up_proj_en": false,
"save_steps": 500,
"micro_batch_size": 4,
"batch_size": 128,
"epochs": 1,
"learning_rate": "3e-4",
"lr_scheduler_type": "linear",
"lora_rank": 128,
"lora_alpha": 256,
"lora_dropout": 0.05,
"cutoff_len": 512,
"dataset": "Alpacazord-V1",
"eval_dataset": "None",
"format": "alpaca-format",
"eval_steps": 100,
"raw_text_file": "None",
"overlap_len": 128,
"newline_favor_len": 128,
"higher_rank_limit": false,
"warmup_steps": 100,
"optimizer": "adamw_torch",
"hard_cut_string": "\\n\\n\\n",
"train_only_after": "",
"stop_at_loss": 0,
"add_eos_token": false,
"min_chars": 0,
"report_to": "None"
}