n_gpu_layers=n_gpu_layers,    n_batch=n_batch,    n_ctx=4096,  # Context window    max_tokens=1000,  # Max tokens to generate    f16_kv=True,  # MUST set to True, otherwise you will run into problem after a couple of calls    callback_manager=callback_manager,    verbose=True,)vectorstore_llama = Chroma(embedding_function=GPT4AllEmbeddings(),persist_directory="./chroma_db_llama")    llama.cpp: loading model from /Users/rlm/Desktop/Code/llama.cpp/llama-2-13b-chat.ggmlv3.q4_0.bin    llama_model_load_internal: format     = ggjt v3 (latest)    llama_model_load_internal: n_vocab    = 32000    llama_model_load_internal: n_ctx      = 4096    llama_model_load_internal: n_embd     = 5120    llama_model_load_internal: n_mult     = 256    llama_model_load_internal: n_head     = 40    llama_model_load_internal: n_layer    = 40    llama_model_load_internal: n_rot      = 128    llama_model_load_internal: freq_base  = 10000.0    llama_model_load_internal: freq_scale = 1    llama_model_load_internal: ftype      = 2 (mostly Q4_0)    llama_model_load_internal: n_ff       = 13824    llama_model_load_internal: model size = 13B    llama_model_load_internal: ggml ctx size =    0.09 MB    llama_model_load_internal: mem required  = 9132.71 MB (+ 1608.00 MB per state)    llama_new_context_with_model: kv self size  = 3200.00 MB    ggml_metal_init: allocating    Found model file at  /Users/rlm/.cache/gpt4all/ggml-all-MiniLM-L6-v2-f16.bin    llama_new_context_with_model: max tensor size =    87.89 MB    ggml_metal_init: using MPS    ggml_metal_init: loading '/Users/rlm/miniforge3/envs/llama/lib/python3.9/site-packages/llama_cpp/ggml-metal.metal'    ggml_metal_init: loaded kernel_add                            0x110fbd600    ggml_metal_init: loaded kernel_mul                            0x110fbeb30    ggml_metal_init: loaded kernel_mul_row                        0x110fbf350    ggml_metal_init: loaded kernel_scale                          0x110fbf9e0    ggml_metal_init: loaded kernel_silu
Given a query, this retriever will:
Given a query, this retriever will: ->: n_gpu_layers=n_gpu_layers,    n_batch=n_batch,    n_ctx=4096,  # Context window    max_tokens=1000,  # Max tokens to generate    f16_kv=True,  # MUST set to True, otherwise you will run into problem after a couple of calls    callback_manager=callback_manager,    verbose=True,)vectorstore_llama = Chroma(embedding_function=GPT4AllEmbeddings(),persist_directory="./chroma_db_llama")    llama.cpp: loading model from /Users/rlm/Desktop/Code/llama.cpp/llama-2-13b-chat.ggmlv3.q4_0.bin    llama_model_load_internal: format     = ggjt v3 (latest)    llama_model_load_internal: n_vocab    = 32000    llama_model_load_internal: n_ctx      = 4096    llama_model_load_internal: n_embd     = 5120    llama_model_load_internal: n_mult     = 256    llama_model_load_internal: n_head     = 40    llama_model_load_internal: n_layer    = 40    llama_model_load_internal: n_rot      = 128    llama_model_load_internal: freq_base  = 10000.0    llama_model_load_internal: freq_scale = 1    llama_model_load_internal: ftype      = 2 (mostly Q4_0)    llama_model_load_internal: n_ff       = 13824    llama_model_load_internal: model size = 13B    llama_model_load_internal: ggml ctx size =    0.09 MB    llama_model_load_internal: mem required  = 9132.71 MB (+ 1608.00 MB per state)    llama_new_context_with_model: kv self size  = 3200.00 MB    ggml_metal_init: allocating    Found model file at  /Users/rlm/.cache/gpt4all/ggml-all-MiniLM-L6-v2-f16.bin    llama_new_context_with_model: max tensor size =    87.89 MB    ggml_metal_init: using MPS    ggml_metal_init: loading '/Users/rlm/miniforge3/envs/llama/lib/python3.9/site-packages/llama_cpp/ggml-metal.metal'    ggml_metal_init: loaded kernel_add                            0x110fbd600    ggml_metal_init: loaded kernel_mul                            0x110fbeb30    ggml_metal_init: loaded kernel_mul_row                        0x110fbf350    ggml_metal_init: loaded kernel_scale                          0x110fbf9e0    ggml_metal_init: loaded kernel_silu