Error when loading rocket-3B-GGUF using text-generation-webui
When loading this model I am getting an error:
Traceback (most recent call last):
File "S:\oobabooga_windows\text-generation-webui\modules\ui_model_menu.py", line 209, in load_model_wrapper
shared.model, shared.tokenizer = load_model(shared.model_name, loader)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "S:\oobabooga_windows\text-generation-webui\modules\models.py", line 85, in load_model
output = load_func_maploader
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "S:\oobabooga_windows\text-generation-webui\modules\models.py", line 249, in llamacpp_loader
model, tokenizer = LlamaCppModel.from_pretrained(model_file)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "S:\oobabooga_windows\text-generation-webui\modules\llamacpp_model.py", line 90, in from_pretrained
result.model = Llama(**params)
^^^^^^^^^^^^^^^
File "S:\oobabooga_windows\text-generation-webui\installer_files\env\Lib\site-packages\llama_cpp_cuda\llama.py", line 365, in init
assert self.model is not None
^^^^^^^^^^^^^^^^^^^^^^
AssertionError
I get the same errors in text-generation-webui. Please guide us.
This is the error I got
GGML_ASSERT: /home/runner/work/llama-cpp-python-cuBLAS-wheels/llama-cpp-python-cuBLAS-wheels/vendor/llama.cpp/ggml.c:13711: tensor->src[0] == NULL || tensor->src[0]->backend == GGML_BACKEND_CPU
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Could not attach to process. If your uid matches the uid of the target
process, check the setting of /proc/sys/kernel/yama/ptrace_scope, or try
again as the root user. For more details, see /etc/sysctl.d/10-ptrace.conf
ptrace: Operation not permitted.
No stack.
The program is not being run.
/arrow/cpp/src/arrow/filesystem/s3fs.cc:2829: arrow::fs::FinalizeS3 was not called even though S3 was initialized. This could lead to a segmentation fault at exit
I downloaded Q6_K version.