metadata
language:
- zh
This checkpoint is a states tuning file from RWKV-6-7B. Please download the base model from https://huggingface.co/BlinkDL/rwkv-6-world/tree/main . It will give a judgement about the type of the sentence. Usage:
- update the latest rwkv package: pip install --upgrade rwkv
- Download the base model and the states file. You may download the states from the epoch_2 directory.
- Following the codes:
- Loading the model and states
from rwkv.model import RWKV
from rwkv.utils import PIPELINE, PIPELINE_ARGS
import torch
# download models: https://huggingface.co/BlinkDL
model = RWKV(model='/media/yueyulin/KINGSTON/models/rwkv6/RWKV-x060-World-7B-v2.1-20240507-ctx4096.pth', strategy='cuda fp16')
print(model.args)
pipeline = PIPELINE(model, "rwkv_vocab_v20230424") # 20B_tokenizer.json is in https://github.com/BlinkDL/ChatRWKV
# use pipeline = PIPELINE(model, "rwkv_vocab_v20230424") for rwkv "world" models
states_file = '/media/yueyulin/data_4t/models/states_tuning/custom_trainer/epoch_2/RWKV-x060-World-7B-v2.1-20240507-ctx4096.pth.pth'
states = torch.load(states_file)
states_value = []
device = 'cuda'
n_head = model.args.n_head
head_size = model.args.n_embd//model.args.n_head
for i in range(model.args.n_layer):
key = f'blocks.{i}.att.time_state'
value = states[key]
prev_x = torch.zeros(model.args.n_embd,device=device,dtype=torch.float16)
prev_states = value.clone().detach().to(device=device,dtype=torch.float16).transpose(1,2)
prev_ffn = torch.zeros(model.args.n_embd,device=device,dtype=torch.float16)
states_value.append(prev_x)
states_value.append(prev_states)
states_value.append(prev_ffn)
The typed schema is :
schema = ['事件', '自然科学', '建筑结构', '地理地区', '组织', '医学', '天文对象', '人造物件', '运输', '作品', '生物', '人物']