metadata
language:
- en
library_name: peft
pipeline_tag: text-generation
tags:
- medical
license: cc-by-nc-4.0
MedFalcon v2 40b LoRA - Final
Model Description
This a model release at 1 epoch
. For evaluation use only! Limitations:
- Do not use to treat paitients! Treat AI content as if you wrote it!!!
Architecture
nmitchko/medfalcon-v2-40b-lora
is a large language model LoRa specifically fine-tuned for medical domain tasks.
It is based on Falcon-40b
at 40 billion parameters.
The primary goal of this model is to improve question-answering and medical dialogue tasks. It was trained using LoRA, specifically QLora, to reduce memory footprint.
See Training Parameters for more info This Lora supports 4-bit and 8-bit modes.
Requirements
bitsandbytes>=0.39.0
peft
transformers
Steps to load this model:
- Load base model using transformers
- Apply LoRA using peft
#
from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers
import torch
from peft import PeftModel
model = "tiiuae/falcon-40b"
LoRA = "nmitchko/medfalcon-v2-40b-lora"
# If you want 8 or 4 bit set the appropriate flags
load_8bit = True
tokenizer = AutoTokenizer.from_pretrained(model)
model = AutoModelForCausalLM.from_pretrained(model,
load_in_8bit=load_8bit,
torch_dtype=torch.float16,
trust_remote_code=True,
)
model = PeftModel.from_pretrained(model, LoRA)
pipeline = transformers.pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
torch_dtype=torch.bfloat16,
trust_remote_code=True,
device_map="auto",
)
sequences = pipeline(
"What does the drug ceftrioxone do?\nDoctor:",
max_length=200,
do_sample=True,
top_k=40,
num_return_sequences=1,
eos_token_id=tokenizer.eos_token_id,
)
for seq in sequences:
print(f"Result: {seq['generated_text']}")
Training Parameters
The model was trained for or 1 epoch on a custom, unreleased dataset named medconcat
.
medconcat
contains only human generated content and weighs in at over 100MiB of raw text.
Item | Amount | Units |
---|---|---|
LoRA Rank | 64 | ~ |
LoRA Alpha | 16 | ~ |
Learning Rate | 1e-4 | SI |
Dropout | 5 | % |