Question: What's the difference between a plain old search engine and an LLM+RAG?
Answer: LLM+RAG provides an experience like semantic search capability plus synthesis but without the need for semantic tagging on the front-end or the back-end.
[https://www.sbert.net/examples/applications/semantic-search/README.html#semantic-search]
Relevance to the Physics Derivation Graph: add the following to an existing large language model (LLM)
- the list of inference rules for the Physics Derivation Graph
- examples of Latex-to-Sage conversion
- example Lean4 proofs
How is "context provision" different from RAG?
What's the difference between a transformer and a model?
specifically
output of help for llama.cpp
docker run -it --rm -v `pwd`:/scratch llama-cpp-with-mistral-7b-v0.1.q6_k:2023-12-22 /bin/bash
root@dc98ac4a23d5:/opt/llama.cpp# ./main -h
usage: ./main [options]
options:
-h, --help show this help message and exit
--version show version and build info
-i, --interactive run in interactive mode
--interactive-first run in interactive mode and wait for input right away
-ins, --instruct run in instruction mode (use with Alpaca models)
-cml, --chatml run in chatml mode (use with ChatML-compatible models)
--multiline-input allows you to write or paste multiple lines without ending each in '\'
-r PROMPT, --reverse-prompt PROMPT
halt generation at PROMPT, return control in interactive mode
(can be specified more than once for multiple prompts).
--color colorise output to distinguish prompt and user input from generations
-s SEED, --seed SEED RNG seed (default: -1, use random seed for < 0)
-t N, --threads N number of threads to use during generation (default: 20)
-tb N, --threads-batch N
number of threads to use during batch and prompt processing (default: same as --threads)
-p PROMPT, --prompt PROMPT
prompt to start generation with (default: empty)
-e, --escape process prompt escapes sequences (\n, \r, \t, \', \", \\)
--prompt-cache FNAME file to cache prompt state for faster startup (default: none)
--prompt-cache-all if specified, saves user input and generations to cache as well.
not supported with --interactive or other interactive options
--prompt-cache-ro if specified, uses the prompt cache but does not update it.
--random-prompt start with a randomized prompt.
--in-prefix-bos prefix BOS to user inputs, preceding the `--in-prefix` string
--in-prefix STRING string to prefix user inputs with (default: empty)
--in-suffix STRING string to suffix after user inputs with (default: empty)
-f FNAME, --file FNAME
prompt file to start generation.
-n N, --n-predict N number of tokens to predict (default: -1, -1 = infinity, -2 = until context filled)
-c N, --ctx-size N size of the prompt context (default: 512, 0 = loaded from model)
-b N, --batch-size N batch size for prompt processing (default: 512)
--samplers samplers that will be used for generation in the order, separated by ';', for example: "top_k;tfs;typical;top_p;min_p;temp"
--sampling-seq simplified sequence for samplers that will be used (default: kfypmt)
--top-k N top-k sampling (default: 40, 0 = disabled)
--top-p N top-p sampling (default: 0.9, 1.0 = disabled)
--min-p N min-p sampling (default: 0.1, 0.0 = disabled)
--tfs N tail free sampling, parameter z (default: 1.0, 1.0 = disabled)
--typical N locally typical sampling, parameter p (default: 1.0, 1.0 = disabled)
--repeat-last-n N last n tokens to consider for penalize (default: 64, 0 = disabled, -1 = ctx_size)
--repeat-penalty N penalize repeat sequence of tokens (default: 1.1, 1.0 = disabled)
--presence-penalty N repeat alpha presence penalty (default: 0.0, 0.0 = disabled)
--frequency-penalty N repeat alpha frequency penalty (default: 0.0, 0.0 = disabled)
--mirostat N use Mirostat sampling.
Top K, Nucleus, Tail Free and Locally Typical samplers are ignored if used.
(default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
--mirostat-lr N Mirostat learning rate, parameter eta (default: 0.1)
--mirostat-ent N Mirostat target entropy, parameter tau (default: 5.0)
-l TOKEN_ID(+/-)BIAS, --logit-bias TOKEN_ID(+/-)BIAS
modifies the likelihood of token appearing in the completion,
i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',
or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'
--grammar GRAMMAR BNF-like grammar to constrain generations (see samples in grammars/ dir)
--grammar-file FNAME file to read grammar from
--cfg-negative-prompt PROMPT
negative prompt to use for guidance. (default: empty)
--cfg-negative-prompt-file FNAME
negative prompt file to use for guidance. (default: empty)
--cfg-scale N strength of guidance (default: 1.000000, 1.0 = disable)
--rope-scaling {none,linear,yarn}
RoPE frequency scaling method, defaults to linear unless specified by the model
--rope-scale N RoPE context scaling factor, expands context by a factor of N
--rope-freq-base N RoPE base frequency, used by NTK-aware scaling (default: loaded from model)
--rope-freq-scale N RoPE frequency scaling factor, expands context by a factor of 1/N
--yarn-orig-ctx N YaRN: original context size of model (default: 0 = model training context size)
--yarn-ext-factor N YaRN: extrapolation mix factor (default: 1.0, 0.0 = full interpolation)
--yarn-attn-factor N YaRN: scale sqrt(t) or attention magnitude (default: 1.0)
--yarn-beta-slow N YaRN: high correction dim or alpha (default: 1.0)
--yarn-beta-fast N YaRN: low correction dim or beta (default: 32.0)
--ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)
--no-penalize-nl do not penalize newline token
--temp N temperature (default: 0.8)
--logits-all return logits for all tokens in the batch (default: disabled)
--hellaswag compute HellaSwag score over random tasks from datafile supplied with -f
--hellaswag-tasks N number of tasks to use when computing the HellaSwag score (default: 400)
--keep N number of tokens to keep from the initial prompt (default: 0, -1 = all)
--draft N number of tokens to draft for speculative decoding (default: 8)
--chunks N max number of chunks to process (default: -1, -1 = all)
-np N, --parallel N number of parallel sequences to decode (default: 1)
-ns N, --sequences N number of sequences to decode (default: 1)
-pa N, --p-accept N speculative decoding accept probability (default: 0.5)
-ps N, --p-split N speculative decoding split probability (default: 0.1)
-cb, --cont-batching enable continuous batching (a.k.a dynamic batching) (default: disabled)
--mmproj MMPROJ_FILE path to a multimodal projector file for LLaVA. see examples/llava/README.md
--image IMAGE_FILE path to an image file. use with multimodal models
--mlock force system to keep model in RAM rather than swapping or compressing
--no-mmap do not memory-map model (slower load but may reduce pageouts if not using mlock)
--numa attempt optimizations that help on some NUMA systems
if run without this previously, it is recommended to drop the system page cache before using this
see https://github.com/ggerganov/llama.cpp/issues/1437
--verbose-prompt print prompt before generation
-dkvc, --dump-kv-cache
verbose print of the KV cache
-nkvo, --no-kv-offload
disable KV offload
-ctk TYPE, --cache-type-k TYPE
KV cache data type for K (default: f16)
-ctv TYPE, --cache-type-v TYPE
KV cache data type for V (default: f16)
--simple-io use basic IO for better compatibility in subprocesses and limited consoles
--lora FNAME apply LoRA adapter (implies --no-mmap)
--lora-scaled FNAME S apply LoRA adapter with user defined scaling S (implies --no-mmap)
--lora-base FNAME optional model to use as a base for the layers modified by the LoRA adapter
-m FNAME, --model FNAME
model path (default: models/7B/ggml-model-f16.gguf)
-md FNAME, --model-draft FNAME
draft model for speculative decoding
-ld LOGDIR, --logdir LOGDIR
path under which to save YAML logs (no logging if unset)
--override-kv KEY=TYPE:VALUE
advanced option to override model metadata by key. may be specified multiple times.
types: int, float, bool. example: --override-kv tokenizer.ggml.add_bos_token=bool:false
log options:
--log-test Run simple logging test
--log-disable Disable trace logs
--log-enable Enable trace logs
--log-file Specify a log filename (without extension)
--log-new Create a separate new log file on start. Each log file will have unique name: "<name>.<ID>.log"
--log-append Don't truncate the old log file.
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