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Developed by: penguintrainer
License: apache-2.0 cc-by-sa-4.0
Finetuned from model : llm-jp/llm-jp-3-13b
Used ichikara-instruction-003-001-1 for fineturning.
ichikara-instruction: 日本語instructionモデル評価データセット © 2023 Akira Sasaki and Masato Hirakawa and Shintaro Horie and Tomoaki Nakamura (CC BY-SA 4.0 )
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Uses
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
BitsAndBytesConfig,
)
from peft import PeftModel
import torch
from tqdm import tqdm
model_id = "llm-jp/llm-jp-3-13b"
adapter_id = "penguintrainer/llm-jp-3-13b-finetune"
# QLoRA config
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16,
)
# Load model
model = AutoModelForCausalLM.from_pretrained(
model_id,
quantization_config=bnb_config,
device_map="auto",
)
# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
# combain LoRA。
model = PeftModel.from_pretrained(model, adapter_id)
text = "大規模言語モデルとは何ですか?"
tokenized_input = tokenizer.encode(text, add_special_tokens=False, return_tensors="pt").to(model.device)
with torch.no_grad():
output = model.generate(
tokenized_input,
max_new_tokens=100,
do_sample=True,
top_p=0.95,
temperature=0.7,
repetition_penalty=1.05,
)[0]
print(tokenizer.decode(output))
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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Model tree for penguintrainer/llm-jp-3-13b-finetune
Base model
llm-jp/llm-jp-3-13b