Can't run inference anymore

A few days ago i could run the inference as normal. Today is just doesn't work anymore.

I downloaded the model and then setup according to the docs.

LOGS:

warning: not compiled with GPU offload support, --gpu-layers option will be ignored
warning: see main README.md for information on enabling GPU BLAS support
build: 3955 (a8ac7072) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_loader: loaded meta data with 24 key-value pairs and 332 tensors from models/BitNet-b1.58-2B-4T/ggml-model-i2_s.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = bitnet-b1.58
llama_model_loader: - kv   1:                               general.name str              = bitnet2b
llama_model_loader: - kv   2:                    bitnet-b1.58.vocab_size u32              = 128256
llama_model_loader: - kv   3:                bitnet-b1.58.context_length u32              = 4096
llama_model_loader: - kv   4:              bitnet-b1.58.embedding_length u32              = 2560
llama_model_loader: - kv   5:                   bitnet-b1.58.block_count u32              = 30
llama_model_loader: - kv   6:           bitnet-b1.58.feed_forward_length u32              = 6912
llama_model_loader: - kv   7:          bitnet-b1.58.rope.dimension_count u32              = 128
llama_model_loader: - kv   8:          bitnet-b1.58.attention.head_count u32              = 20
llama_model_loader: - kv   9:       bitnet-b1.58.attention.head_count_kv u32              = 5
llama_model_loader: - kv  10:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  11: bitnet-b1.58.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  12:                bitnet-b1.58.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  13:                          general.file_type u32              = 40
llama_model_loader: - kv  14:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,128256]  = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  18:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  19:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  20:                tokenizer.ggml.eos_token_id u32              = 128001
llama_model_loader: - kv  21:            tokenizer.ggml.padding_token_id u32              = 128001
llama_model_loader: - kv  22:                    tokenizer.chat_template str              = {% for message in messages %}{% if lo...
llama_model_loader: - kv  23:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  121 tensors
llama_model_loader: - type  f16:    1 tensors
llama_model_loader: - type i2_s:  210 tensors
llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'bitnet-b1.58'
llama_load_model_from_file: failed to load model
common_init_from_params: failed to load model 'models/BitNet-b1.58-2B-4T/ggml-model-i2_s.gguf'
main: error: unable to load model
Error occurred while running command: Command '['build/bin/llama-cli', '-m', 'models/BitNet-b1.58-2B-4T/ggml-model-i2_s.gguf', '-n', '128', '-t', '2', '-p', 'Hi', '-ngl', '0', '-c', '2048', '--temp', '0.8', '-b', '1', '-cnv']' returned non-zero exit status 1.

Reproduce the failure with models/BitNet-b1.58-2B-4T/ggml-model-i2_s.gguf and the shown build/bin/llama-cli command. Start by checking the README guidance and the model-loading output around the unknown bitnet-b1.58 architecture. Done means the downloaded model loads and inference completes without the architecture error.