from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="HauhauCS/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive",
filename="Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-BF16.gguf",
)
ValueError Traceback (most recent call last)
[/tmp/ipykernel_1917/696730726.py](https://localhost:8080/#) in <cell line: 0>()
3 from llama_cpp import Llama
4
----> 5 llm = Llama.from_pretrained(
6 repo_id="HauhauCS/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive",
7 filename="Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-BF16.gguf",
2 frames
[/usr/local/lib/python3.12/dist-packages/llama_cpp/_internals.py](https://localhost:8080/#) in __init__(self, path_model, params, verbose)
56
57 if model is None:
---> 58 raise ValueError(f"Failed to load model from file: {path_model}")
59
60 vocab = llama_cpp.llama_model_get_vocab(model)
ValueError: Failed to load model from file: /root/.cache/huggingface/hub/models--HauhauCS--Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive/snapshots/53367faad177ee6a23601983cdac4308b51393df/./Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-BF16.gguf
This error message is not actionable as it doesn't say why it failed to load so the user can't do much about it.
Repro steps:
Generated code is:
which fails with:
This error message is not actionable as it doesn't say why it failed to load so the user can't do much about it.