VMware/open-llama-13B-open-instruct

Instruction-tuned version of the fully trained Open LLama 13B model. The model is open for COMMERCIAL USE.

注意：该模型是使用Alpaca提示模板进行训练的。注意：快速分词器会导致错误的编码，当实例化分词器时，请将use_fast = False参数设置为false。注意：由于分词器会合并多个空格，因此该模型可能在处理代码时遇到困难

许可

• 商业可行
• Instruction数据集 VMware/open-instruct-v1-oasst-dolly-hhrlhf 属于cc-by-sa-3.0
• 语言模型（ openlm-research/open_llama_13b ）属于apache-2.0

术语

• 模型：Open-llama
• 模型大小：13B参数
• 数据集：Open-instruct-v1（oasst，dolly，hhrlhf）

在Transformers中使用

import os
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = 'VMware/open-llama-13b-open-instruct'


tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)

model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map='sequential')

prompt_template = "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:"

prompt = 'Explain in simple terms how the attention mechanism of a transformer model works'


inputt = prompt_template.format(instruction= prompt)
input_ids = tokenizer(inputt, return_tensors="pt").input_ids.to("cuda")

output1 = model.generate(input_ids, max_length=512)
input_length = input_ids.shape[1]
output1 = output1[:, input_length:]
output = tokenizer.decode(output1[0])

print(output)

微调细节

微调脚本将在我们的 RAIL Github Repository 中提供

评估

TODO