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llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this
llama.cpp: loading model from ./models/ggml-model-q4_0.bin llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this llama_model_load_internal: format = 'ggml' (old version with low tokenizer quality and no mmap support) llama_model_load_internal: n_vocab = 32000 llama_model_load_internal: n_ctx = 512 llama_model_load_internal: n_embd = 4096 llama_model_load_internal: n_mult = 256 llama_model_load_internal: n_head = 32 llama_model_load_internal: n_layer = 32 llama_model_load_internal: n_rot = 128 llama_model_load_internal: ftype = 2 (mostly Q4_0) llama_model_load_internal: n_ff = 11008 llama_model_load_internal: n_parts = 1 llama_model_load_internal: model size = 7B llama_model_load_internal: ggml ctx size = 4113739.11 KB llama_model_load_internal: mem required = 5809.32 MB (+ 2052.00 MB per state) ................................................................................................... I am using a recommended model, but I get this error message. How do you think I could solve it?
Is this the full output? If not - please post the full output
(privategpt) root@alienware17B:/home/rex/privateGPT# python privateGPT.py llama.cpp: loading model from ./models/ggml-model-q4_0.bin llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this llama_model_load_internal: format = 'ggml' (old version with low tokenizer quality and no mmap support) llama_model_load_internal: n_vocab = 32000 llama_model_load_internal: n_ctx = 512 llama_model_load_internal: n_embd = 4096 llama_model_load_internal: n_mult = 256 llama_model_load_internal: n_head = 32 llama_model_load_internal: n_layer = 32 llama_model_load_internal: n_rot = 128 llama_model_load_internal: ftype = 2 (mostly Q4_0) llama_model_load_internal: n_ff = 11008 llama_model_load_internal: n_parts = 1 llama_model_load_internal: model size = 7B llama_model_load_internal: ggml ctx size = 4113739.11 KB llama_model_load_internal: mem required = 5809.32 MB (+ 2052.00 MB per state) ................................................................................................... . llama_init_from_file: kv self size = 512.00 MB AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | VSX = 0 | Using embedded DuckDB with persistence: data will be stored in: db gptj_model_load: loading model from './models/ggml-gpt4all-j-v1.3-groovy.bin' - please wait ... gptj_model_load: n_vocab = 50400 gptj_model_load: n_ctx = 2048 gptj_model_load: n_embd = 4096 gptj_model_load: n_head = 16 gptj_model_load: n_layer = 28 gptj_model_load: n_rot = 64 gptj_model_load: f16 = 2 gptj_model_load: ggml ctx size = 4505.45 MB gptj_model_load: memory_size = 896.00 MB, n_mem = 57344 gptj_model_load: ................................... done gptj_model_load: model size = 3609.38 MB / num tensors = 285 Enter a query:
I got the same messages.
(venv) my@laptop:~/privateGPT$ python privateGPT.py llama.cpp: loading model from ./models/ggml-model-q4_0.bin llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this llama_model_load_internal: format = 'ggml' (old version with low tokenizer quality and no mmap support) llama_model_load_internal: n_vocab = 32000 llama_model_load_internal: n_ctx = 512 llama_model_load_internal: n_embd = 4096 llama_model_load_internal: n_mult = 256 llama_model_load_internal: n_head = 32 llama_model_load_internal: n_layer = 32 llama_model_load_internal: n_rot = 128 llama_model_load_internal: ftype = 2 (mostly Q4_0) llama_model_load_internal: n_ff = 11008 llama_model_load_internal: n_parts = 1 llama_model_load_internal: model size = 7B llama_model_load_internal: ggml ctx size = 4113748.20 KB llama_model_load_internal: mem required = 5809.33 MB (+ 2052.00 MB per state) ................................................................................................... . llama_init_from_file: kv self size = 512.00 MB AVX = 1 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | VSX = 0 | Using embedded DuckDB with persistence: data will be stored in: db Illegal instruction (core dumped)
I got the same errors
(privategpt) root@alienware17B:/home/rex/privateGPT# python privateGPT.py llama.cpp: loading model from ./models/ggml-model-q4_0.bin llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this llama_model_load_internal: format = 'ggml' (old version with low tokenizer quality and no mmap support) llama_model_load_internal: n_vocab = 32000 llama_model_load_internal: n_ctx = 512 llama_model_load_internal: n_embd = 4096 llama_model_load_internal: n_mult = 256 llama_model_load_internal: n_head = 32 llama_model_load_internal: n_layer = 32 llama_model_load_internal: n_rot = 128 llama_model_load_internal: ftype = 2 (mostly Q4_0) llama_model_load_internal: n_ff = 11008 llama_model_load_internal: n_parts = 1 llama_model_load_internal: model size = 7B llama_model_load_internal: ggml ctx size = 4113739.11 KB llama_model_load_internal: mem required = 5809.32 MB (+ 2052.00 MB per state) ................................................................................................... . llama_init_from_file: kv self size = 512.00 MB AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | VSX = 0 | Using embedded DuckDB with persistence: data will be stored in: db gptj_model_load: loading model from './models/ggml-gpt4all-j-v1.3-groovy.bin' - please wait ... gptj_model_load: n_vocab = 50400 gptj_model_load: n_ctx = 2048 gptj_model_load: n_embd = 4096 gptj_model_load: n_head = 16 gptj_model_load: n_layer = 28 gptj_model_load: n_rot = 64 gptj_model_load: f16 = 2 gptj_model_load: ggml ctx size = 4505.45 MB gptj_model_load: memory_size = 896.00 MB, n_mem = 57344 gptj_model_load: ................................... done gptj_model_load: model size = 3609.38 MB / num tensors = 285 Enter a query:
That seems to be working, Look at "Enter a query:". I always get the message about mmap because I use old llama7b and 13b models. I just ignore it.
@alxspiker I'm getting the error at the ingestion step:
llama.cpp: loading model from ./models/ggml-model-q4_0.bin
llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this
llama_model_load_internal: format = 'ggml' (old version with low tokenizer quality and no mmap support)
llama_model_load_internal: n_vocab = 32000
llama_model_load_internal: n_ctx = 512
llama_model_load_internal: n_embd = 4096
llama_model_load_internal: n_mult = 256
llama_model_load_internal: n_head = 32
llama_model_load_internal: n_layer = 32
llama_model_load_internal: n_rot = 128
llama_model_load_internal: ftype = 2 (mostly Q4_0)
llama_model_load_internal: n_ff = 11008
llama_model_load_internal: n_parts = 1
llama_model_load_internal: model size = 7B
llama_model_load_internal: ggml ctx size = 4113748.20 KB
llama_model_load_internal: mem required = 5809.33 MB (+ 2052.00 MB per state)
terminate called after throwing an instance of 'std::bad_alloc'
what(): std::bad_alloc
Aborted (core dumped)```
I get this error too.
I get the same error and the embedding process takes a while for the state of the union doc. My machines heats up and fan blows at full speed. I've a M2 MAX with 38 core and 64GB of memory. Inference also takes a long time to and it crashes after 2-3 questions.
I get the same error. Any quick help to sort out this error is greatly appreciated.
llama.cpp: loading model from models/ggml-model-q4_0.bin llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this llama_model_load_internal: format = 'ggml' (old version with low tokenizer quality and no mmap support) I get the same error. Any quick help to sort out this error is greatly appreciated.
Same error...
same here
This is the error I'm getting:
main: build = 553 (63d2046) main: seed = 1684182263 llama.cpp: loading model from ggml-alpaca-7b-native-q4.bin llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this llama_model_load_internal: format = ggmf v1 (old version with no mmap support) llama_model_load_internal: n_vocab = 32000 llama_model_load_internal: n_ctx = 512 llama_model_load_internal: n_embd = 4096 llama_model_load_internal: n_mult = 256 llama_model_load_internal: n_head = 32 llama_model_load_internal: n_layer = 32 llama_model_load_internal: n_rot = 128 llama_model_load_internal: ftype = 2 (mostly Q4_0) llama_model_load_internal: n_ff = 11008 llama_model_load_internal: n_parts = 1 llama_model_load_internal: model size = 7B error loading model: this format is no longer supported (see https://github.com/ggerganov/llama.cpp/pull/1305) llama_init_from_file: failed to load model llama_init_from_gpt_params: error: failed to load model 'ggml-alpaca-7b-native-q4.bin' main: error: unable to load model
main: build = 553 (63d2046) main: seed = 1684197811 llama.cpp: loading model from ./models/ggml-model-q4_1.bin llama_model_load_internal: format = ggjt v1 (pre #1405) llama_model_load_internal: n_vocab = 32000 llama_model_load_internal: n_ctx = 512 llama_model_load_internal: n_embd = 6656 llama_model_load_internal: n_mult = 256 llama_model_load_internal: n_head = 52 llama_model_load_internal: n_layer = 60 llama_model_load_internal: n_rot = 128 llama_model_load_internal: ftype = 3 (mostly Q4_1) llama_model_load_internal: n_ff = 17920 llama_model_load_internal: n_parts = 1 llama_model_load_internal: model size = 30B error loading model: this format is no longer supported (see https://github.com/ggerganov/llama.cpp/pull/1305) llama_init_from_file: failed to load model llama_init_from_gpt_params: error: failed to load model './models/ggml-model-q4_1.bin' main: error: unable to load model
Same issue Loading documents from source_documents Loaded 28 documents from source_documents Split into 2405 chunks of text (max. 500 tokens each) llama.cpp: loading model from models/ggml-model-q4_0.bin llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this llama_model_load_internal: format = 'ggml' (old version with low tokenizer quality and no mmap support) llama_model_load_internal: n_vocab = 32000 llama_model_load_internal: n_ctx = 1000 llama_model_load_internal: n_embd = 4096 llama_model_load_internal: n_mult = 256 llama_model_load_internal: n_head = 32 llama_model_load_internal: n_layer = 32 llama_model_load_internal: n_rot = 128 llama_model_load_internal: ftype = 2 (mostly Q4_0) llama_model_load_internal: n_ff = 11008 llama_model_load_internal: n_parts = 1 llama_model_load_internal: model size = 7B llama_model_load_internal: ggml ctx size = 4113748.20 KB llama_model_load_internal: mem required = 5809.33 MB (+ 2052.00 MB per state)
what's the cause?
ecs-user@mimiako:~/privateGPT$ python3 ./privateGPT.py
llama.cpp: loading model from /home/ecs-user/privateGPT/downloadedFiles/ggml-model-q4_0.bin
llama.cpp: can't use mmap because tensors are not aligned; convert to new format to avoid this
llama_model_load_internal: format = 'ggml' (old version with low tokenizer quality and no mmap support)
llama_model_load_internal: n_vocab = 32000
llama_model_load_internal: n_ctx = 1000
llama_model_load_internal: n_embd = 4096
llama_model_load_internal: n_mult = 256
llama_model_load_internal: n_head = 32
llama_model_load_internal: n_layer = 32
llama_model_load_internal: n_rot = 128
llama_model_load_internal: ftype = 2 (mostly Q4_0)
llama_model_load_internal: n_ff = 11008
llama_model_load_internal: n_parts = 1
llama_model_load_internal: model size = 7B
llama_model_load_internal: ggml ctx size = 4113748.20 KB
llama_model_load_internal: mem required = 5809.33 MB (+ 2052.00 MB per state)
...................................................................................................
.
llama_init_from_file: kv self size = 1000.00 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 = 0 | SSE3 = 1 | VSX = 0 |
Using embedded DuckDB with persistence: data will be stored in: /home/ecs-user/privateGPT/vector/
gptj_model_load: loading model from '/home/ecs-user/privateGPT/downloadedFiles/ggml-gpt4all-j-v1.3-groovy.bin' - please wait ...
gptj_model_load: n_vocab = 50400
gptj_model_load: n_ctx = 2048
gptj_model_load: n_embd = 4096
gptj_model_load: n_head = 16
gptj_model_load: n_layer = 28
gptj_model_load: n_rot = 64
gptj_model_load: f16 = 2
gptj_model_load: ggml ctx size = 4505.45 MB
gptj_model_load: memory_size = 896.00 MB, n_mem = 57344
gptj_model_load: ...........................Killed
some of the errors here relate to memory - as in the host system does not have enough memory. When you see "Killed" it looks like the kernel killed the process (python) due to lack of memory
Run a dmesg or check /var/log/messages for more information
same error
I redownloaded the model and embeddings file, and it goes through after that.
@kkski What do you mean by "goes through" after you redownloaded the models?
We are not using llama.cpp as the embeddings model anymore. Plus, ingest got a LOT faster with the use of the new embeddings model #224
Note: this is a breaking change, any existing database will stop working with the new changes. You'll need to re-ingest your docs. It is recommended as the process is faster and the results are better.