abetlen / abetlen/llama-cpp-python
generation hangs forever
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Descrição
# Prerequisites
Please answer the following questions for yourself before submitting an issue.
- [x] I am running the latest code. Development is very rapid so there are no tagged versions as of now.
- [x] I carefully followed the [README.md](https://github.com/abetlen/llama-cpp-python/blob/main/README.md).
- [x] I [searched using keywords relevant to my issue](https://docs.github.com/en/issues/tracking-your-work-with-issues/filtering-and-searching-issues-and-pull-requests) to make sure that I am creating a new issue that is not already open (or closed).
- [x] I reviewed the [Discussions](https://github.com/abetlen/llama-cpp-python/discussions), and have a new bug or useful enhancement to share.
# Expected Behavior
The following code should print the output
```
from llama_cpp import Llama
llm = Llama(model_path="/scratch/yerong/.cache/pyllama/Llama-2-7b/ggml-model-q4_0.gguf", n_gpu_layers= 100, n_ctx=100)
output = llm("Q: Name the planets in the solar system? A: ", max_tokens=32, stop=["Q:", "\n"], echo=True)
print(output)
```
# Current Behavior
**Currently it hangs forever**
```
llm_load_print_meta: model ftype = mostly Q4_0
llm_load_print_meta: model size = 6.74 B
llm_load_print_meta: general.name = LLaMA v2
llm_load_print_meta: BOS token = 1 ''
llm_load_print_meta: EOS token = 2 ''
llm_load_print_meta: UNK token = 0 ''
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.09 MB
llm_load_tensors: using CUDA for GPU acceleration
llm_load_tensors: mem required = 70.41 MB (+ 50.00 MB per state)
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloading v cache to GPU
llm_load_tensors: offloading k cache to GPU
llm_load_tensors: offloaded 35/35 layers to GPU
llm_load_tensors: VRAM used: 3628 MB
..................................................................................................
llama_new_context_with_model: kv self size = 50.00 MB
llama_new_context_with_model: compute buffer total size = 15.24 MB
llama_new_context_with_model: VRAM scratch buffer: 13.77 MB
AVX = 1 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | S
SE3 = 1 | SSSE3 = 1 | VSX = 0 |
```

# Environment and Context
Please provide detailed information about your computer setup. This is important in case the issue is not reproducible except for under certain specific conditions.
* SDK version, e.g. for Linux:
```
(lla) [yerong2@ccc0351 self-instruct]$ python3 --version
Python 3.11.4
(lla) [yerong2@ccc0351 self-instruct]$ make --version
GNU Make 3.82
Built for x86_64-redhat-linux-gnu
Copyright (C) 2010 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.
(lla) [yerong2@ccc0351 self-instruct]$ g++ --version
g++ (GCC) 11.2.0
Copyright (C) 2021 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
```
# Failure Information (for bugs)
Please help provide information about the failure if this is a bug. If it is not a bug, please remove the rest of this template.
# Steps to Reproduce
Please provide detailed steps for reproducing the issue. We are not sitting in front of your screen, so the more detail the better.
1.
```
make clean;make LLAMA_CUBLAS=1 -j libllama.so
cp libllama.so /scratch/yerong/.conda/envs/lla/lib/python3.11/site-packages/llama_cpp
```
2.
```
from llama_cpp import Llama
llm = Llama(model_path="/scratch/yerong/.cache/pyllama/Llama-2-7b/ggml-model-q4_0.gguf", n_gpu_layers= 100, n_ctx=100)
output = llm("Q: Name the planets in the solar system? A: ", max_tokens=32, stop=["Q:", "\n"], echo=True)
print(output)
```
**Note: Many issues seem to be regarding functional or performance issues / differences with `llama.cpp`. In these cases we need to confirm that you're comparing against the version of `llama.cpp` that was built with your python package, and which parameters you're passing to the context.**
Try the following:
1. `git clone https://github.com/abetlen/llama-cpp-python`
2. `cd llama-cpp-python`
3. `rm -rf _skbuild/` # delete any old builds
4. `python setup.py develop`
5. `cd ./vendor/llama.cpp`
6. Follow [llama.cpp's instructions](https://github.com/ggerganov/llama.cpp#build) to `cmake` llama.cpp
7. Run llama.cpp's `./main` with the same arguments you previously passed to llama-cpp-python and see if you can reproduce the issue. If you can, [log an issue with llama.cpp](https://github.com/ggerganov/llama.cpp/issues)
# Failure Logs
Please include any relevant log snippets or files. If it works under one configuration but not under another, please provide logs for both configurations and their corresponding outputs so it is easy to see where behavior changes.
Also, please try to **avoid using screenshots** if at all possible. Instead, copy/paste the console output and use [Github's markdown](https://docs.github.com/en/get-started/writing-on-github/getting-started-with-writing-and-formatting-on-github/basic-writing-and-formatting-syntax) to cleanly format your logs for easy readability.
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