cohere2 architecture issue

### Description
I'm encountering an error when trying to use the CohereForAI/c4ai-command-r7b-12-2024 GGUF model with llama-cpp-python. The error indicates that the cohere2 architecture is not recognized.

### Environment
- Platform: Google Colab
- Package: llama-cpp-python (via llama-index-llms-llama-cpp)
- Model: c4ai-command-r7b-12-2024 GGUF version
- CUDA Version: 12.2

### Code
```python
from llama_index.llms.llama_cpp import LlamaCPP

def initialize_llm(model_path, temperature=0.9, max_new_tokens=1000, context_window=8192):
llm = LlamaCPP(
model_url=model_path,
temperature=temperature,
max_new_tokens=max_new_tokens,
context_window=context_window,
messages_to_prompt=messages_to_prompt,
completion_to_prompt=completion_to_prompt,
generate_kwargs={
"min_p": 0.2,
},
model_kwargs={
"n_gpu_layers": -1,
"n_batch": 512,
"n_threads": 96,
"n_ctx": context_window,
},
verbose=True
)
return llm

llm = initialize_llm("https://huggingface.co/dranger003/c4ai-command-r7b-12-2024-GGUF/resolve/main/ggml-c4ai-command-r7b-12-2024-q4_k.gguf")

Downloading url https://huggingface.co/dranger003/c4ai-command-r7b-12-2024-GGUF/resolve/main/ggml-c4ai-command-r7b-12-2024-q4_k.gguf to path /tmp/llama_index/models/ggml-c4ai-command-r7b-12-2024-q4_k.gguf
total size (MB): 5057.01
4823it [03:30, 22.89it/s]
llama_model_loader: loaded meta data with 38 key-value pairs and 258 tensors from /tmp/llama_index/models/ggml-c4ai-command-r7b-12-2024-q4_k.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 = cohere2
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = C4AI Command R7B
llama_model_loader: - kv 3: general.size_label str = 8.0B
llama_model_loader: - kv 4: general.license str = cc-by-nc-4.0
llama_model_loader: - kv 5: general.languages arr[str,23] = ["en", "fr", "de", "es", "it", "pt", ...
llama_model_loader: - kv 6: cohere2.block_count u32 = 32
llama_model_loader: - kv 7: cohere2.context_length u32 = 8192
llama_model_loader: - kv 8: cohere2.embedding_length u32 = 4096
llama_model_loader: - kv 9: cohere2.feed_forward_length u32 = 14336
llama_model_loader: - kv 10: cohere2.attention.head_count u32 = 32
llama_model_loader: - kv 11: cohere2.attention.head_count_kv u32 = 8
llama_model_loader: - kv 12: cohere2.rope.freq_base f32 = 50000.000000
llama_model_loader: - kv 13: cohere2.attention.layer_norm_epsilon f32 = 0.000010
llama_model_loader: - kv 14: cohere2.attention.key_length u32 = 128
llama_model_loader: - kv 15: cohere2.attention.value_length u32 = 128
llama_model_loader: - kv 16: general.file_type u32 = 15
llama_model_loader: - kv 17: cohere2.logit_scale f32 = 0.250000
llama_model_loader: - kv 18: cohere2.attention.sliding_window u32 = 4096
llama_model_loader: - kv 19: cohere2.vocab_size u32 = 256000
llama_model_loader: - kv 20: cohere2.rope.dimension_count u32 = 128
llama_model_loader: - kv 21: cohere2.rope.scaling.type str = none
llama_model_loader: - kv 22: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 23: tokenizer.ggml.pre str = command-r
llama_model_loader: - kv 24: tokenizer.ggml.tokens arr[str,256000] = ["", "", "", "", ...
llama_model_loader: - kv 25: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, ...
llama_model_loader: - kv 26: tokenizer.ggml.merges arr[str,253333] = ["Ġ Ġ", "Ġ t", "e r", "i n", "Ġ a...
llama_model_loader: - kv 27: tokenizer.ggml.bos_token_id u32 = 5
llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 255001
llama_model_loader: - kv 29: tokenizer.ggml.unknown_token_id u32 = 1
llama_model_loader: - kv 30: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = true
llama_model_loader: - kv 32: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 33: tokenizer.chat_template.tool_use str = {%- macro document_turn(documents) -%...
llama_model_loader: - kv 34: tokenizer.chat_template.rag str = {% set tools = [] %}\n{%- macro docume...
llama_model_loader: - kv 35: tokenizer.chat_templates arr[str,2] = ["tool_use", "rag"]
llama_model_loader: - kv 36: tokenizer.chat_template str = {% if documents %}\n{% set tools = [] ...
llama_model_loader: - kv 37: general.quantization_version u32 = 2
llama_model_loader: - type f32: 33 tensors
llama_model_loader: - type q4_K: 192 tensors
llama_model_loader: - type q6_K: 33 tensors
llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'cohere2'
llama_load_model_from_file: failed to load model

Error Message
llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'cohere2'
llama_load_model_from_file: failed to load model

ValueError: Failed to load model from file: /tmp/llama_index/models/ggml-c4ai-command-r7b-12-2024-q4_k.gguf