binary-husky/gpt_academic · critical · RuntimeError
不能正常加载jittorllms的参数!
Error message
不能正常加载jittorllms的参数!
What it means
Loader failure for the ChatRWKV variant of JittorLLMs: get_model(types.SimpleNamespace(model='chatrwkv')) raised in the loader subprocess; the bare except sends '[Local Message] Call jittorllms fail' to the parent and re-raises RuntimeError('不能正常加载jittorllms的参数!'), hiding the original exception.
Source
Thrown at request_llms/bridge_jittorllms_rwkv.py:65
root_dir_assume = os.path.abspath(os.path.dirname(__file__) + '/..')
os.chdir(root_dir_assume + '/request_llms/jittorllms')
sys.path.append(root_dir_assume + '/request_llms/jittorllms')
validate_path() # validate path so you can run from base directory
def load_model():
import types
try:
if self.jittorllms_model is None:
device = get_conf('LOCAL_MODEL_DEVICE')
from .jittorllms.models import get_model
# available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
args_dict = {'model': 'chatrwkv'}
print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
print('done get model')
except:
self.child.send('[Local Message] Call jittorllms fail 不能正常加载jittorllms的参数。')
raise RuntimeError("不能正常加载jittorllms的参数!")
print('load_model')
load_model()
# 进入任务等待状态
print('进入任务等待状态')
while True:
# 进入任务等待状态
kwargs = self.child.recv()
query = kwargs['query']
history = kwargs['history']
# 是否重置
if len(self.local_history) > 0 and len(history)==0:
print('触发重置')
self.jittorllms_model.reset()
self.local_history.append(query)
print('收到消息,开始请求')
try:View on GitHub (pinned to d6bde0fa54)
Solutions
- Run `python -c "from request_llms.jittorllms.models import get_model; import types; get_model(types.SimpleNamespace(model='chatrwkv'))"` to surface the real error.
- Install jittorllms requirements and ensure the RWKV weights download completes (network/disk).
- Check LOCAL_MODEL_DEVICE and GPU memory; try cpu to smoke-test.
- Prefer a maintained RWKV runtime (e.g. rwkv.cpp / ChatRWKV directly) over the legacy jittorllms bridge.
Defensive patterns
Strategy: validation
Validate before calling
def jittorllms_available(model: str) -> bool:
try:
from request_llms.jittorllms.models import get_model # noqa
return True
except Exception:
return False Try / catch
try:
handle = GetGLMHandle()
except RuntimeError as e:
if 'jittorllms' in str(e):
log.error('chatrwkv load failed: %s', e) Prevention
- Pre-fetch RWKV weights; verify disk space
- Smoke-test get_model(model='chatrwkv') in isolation
- Prefer maintained RWKV runtimes over the legacy jittorllms bridge
When it happens
Trigger: First load of local chatrwkv: jittorllms submodule/deps missing, RWKV checkpoint download failure, CUDA/Jittor init error, wrong LOCAL_MODEL_DEVICE.
Common situations: Environment without the jittorllms assets, offline machine, driver/Jittor mismatch, insufficient VRAM for the RWKV weights.
Related errors
AI-assisted analysis of binary-husky/gpt_academic@d6bde0fa54 (2026-08-14).
Data as JSON: /api/errors/1e0d1e8a62e29a89.
Report an issue: GitHub.