ๅ ๅ ฅไธญๆ่ฏ่กจๅนถ็ปง็ปญ้ข่ฎญ็ปไธญๆEmbedding๏ผๅนถๅจๆญคๅบ็กไธ็ปง็ปญไฝฟ็จๆไปคๆฐๆฎ้finetuning๏ผๅพๅฐ็ไธญๆAlpaca-33Bๆจกๅใ
ๆจกๅ่ฝฌๆข็จๅฐ็็ธๅ ณbaseๅloraๆจกๅๅฆไธ๏ผ
- base-model: elinas/llama-30b-hf-transformers-4.29
- lora-model: ziqingyang/chinese-alpaca-lora-33b
่ฏฆๆ ๅฏๅ่๏ผhttps://github.com/ymcui/Chinese-LLaMA-Alpaca/releases/tag/v4.0
ไฝฟ็จๆนๆณๅ่
- ๅฎ่ฃ ๆจกๅๅ
pip install sentencepiece
pip install transformers>=4.28.0
- ็ๆๆๆฌ
import torch
import transformers
from transformers import LlamaTokenizer, LlamaForCausalLM
def generate_prompt(text):
return f"""Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{text}
### Response:"""
tokenizer = LlamaTokenizer.from_pretrained('minlik/chinese-alpaca-33b-merged')
model = LlamaForCausalLM.from_pretrained('minlik/chinese-alpaca-33b-merged').half().to('cuda')
model.eval()
text = '็ฌฌไธไธช็ปไธๆ็็ไบบๆฏ่ฐ๏ผ'
prompt = generate_prompt(text)
input_ids = tokenizer.encode(prompt, return_tensors='pt').to('cuda')
with torch.no_grad():
output_ids = model.generate(
input_ids=input_ids,
max_new_tokens=128,
temperature=1,
top_k=40,
top_p=0.9,
repetition_penalty=1.15
).cuda()
output = tokenizer.decode(output_ids[0], skip_special_tokens=True)
print(output.replace(prompt, '').strip())
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 53.09 |
ARC (25-shot) | 59.3 |
HellaSwag (10-shot) | 78.43 |
MMLU (5-shot) | 57.69 |
TruthfulQA (0-shot) | 52.45 |
Winogrande (5-shot) | 76.09 |
GSM8K (5-shot) | 8.04 |
DROP (3-shot) | 39.67 |
- Downloads last month
- 1,463
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.