- added functionality to find the smallest fitting buffer instead of the first found buffer that >= than requested
-- this prevents that two buffer allocations in sequence can take a huge buffer for a small tensor and then require a new buffer for the 2nd tensor
-- in my test it saved 1GB VRAM that are now free for more offloading
cuda free buffers:
- added a helper function that frees all unused buffers from a device to prevent huge F32 buffers from cuBLAS occupying VRAM needlessly after token ingestion
libfalcon:
- corrected vram_overhead calculation to account for the actual non-weight buffers needed during inference
- added vram_overhead for n_batch > 1 as this switches the ingestion into a 32 bit dequantization mode for cu_blas which needs almost 2 GB VRAM buffers
- corrected the automated layer distribution to fill VRAM as much as possible with layers
From here on it's recommended to use --ngl 100 and -b 1 for CUDA processing.
In addition -t is recommended using 1 or 1 less threads than CPU cores (depends on CPU, GPU used)
- disabled offload of non layer tensors for now (not working yet)
- corrected tensor size calculation for vram
- added some more detailed vram reporting
- added a automated skip of tensors that would not fit in vram (significant slowdown if --ngl is too high, probably from temporary cuda buffer copies)
- added vram_overhead and vram_reserved - those are not pretty but currently needed to get the vram usage right
- moved vram scratch buffer allocation a bit up so the usage is available for the skip
Added falcon main and library based on llama.cpp
CPU inference works (getting ~260ms/token on 7B 16 bit falcon)
Tested with 7B 16 bit and the two shakespear models (both in 16 bit precisiononly)
TODO/WIP:
1) quantization runs, creates a ggjt 3 file but something is wrong with the quantized model binary
- even quantization from 16 -> 16 also fails, something is wrong in the tensors produced
2) mmap should work with quantized binaries once 1) is solved
3) CUDA support is mostly there, it's currently disabled (all CPU backend)
4) memory/context caluculations are off, GPU memory calculations are wrong either
5) the python conversion script is pre GGML 1 version (tokens without scores)
6) some stuff is still called "llama", some of it should be renamed to a generic name as it works for both
7) the GGML produced by the current python uses an old ftype method
Makfiles:
cmake on windows with build tools works
the makefile for linux/msys was blind adjusted but not tested yet - possibly missed something
Changes to the codebase:
* repeat2 has been added to ggml (jploski - https://github.com/ggerganov/ggml/pull/231) including the backward variant (untested, probably fails)
* minor changes to work with falcon (name length)
* libfalcon is the previous "llama.cpp" and falcon_main is the previous main.cpp
A major rewrite for the server example.
Note that if you have built something on the previous server API, it will probably be incompatible.
Check out the examples for how a typical chat app could work.
This took a lot of effort, there are 24 PR's closed in the submitter's repo alone, over 160 commits and a lot of comments and testing.
Summary of the changes:
- adds missing generation parameters: tfs_z, typical_p, repeat_last_n, repeat_penalty, presence_penalty, frequency_penalty, mirostat, penalize_nl, seed, ignore_eos
- applies missing top k sampler
- removes interactive mode/terminal-like behavior, removes exclude parameter
- moves threads and batch size to server command-line parameters
- adds LoRA loading and matches command line parameters with main example
- fixes stopping on EOS token and with the specified token amount with n_predict
- adds server timeouts, host, and port settings
- adds expanded generation complete response; adds generation settings, stop reason, prompt truncated, model used, and final text
- sets defaults for unspecified parameters between requests
- removes /next-token endpoint and as_loop parameter, adds stream parameter and server-sent events for streaming
- adds CORS headers to responses
- adds request logging, exception printing and optional verbose logging
- adds better stopping words handling when matching multiple tokens and while streaming, or when it finishes on a partial stop string
- adds printing an error when it can't bind to the host/port specified
- fixes multi-byte character handling and replaces invalid UTF-8 characters on responses
- prints timing and build info on startup
- adds logit bias to request parameters
- removes embedding mode
- updates documentation; adds streaming Node.js and Bash examples
- fixes code formatting
- sets server threads to 1 since the current global state doesn't work well with simultaneous requests
- adds truncation of the input prompt and better context reset
- removes token limit from the input prompt
- significantly simplified the logic and removed a lot of variables
---------
Co-authored-by: anon998 <131767832+anon998@users.noreply.github.com>
Co-authored-by: Henri Vasserman <henv@hot.ee>
Co-authored-by: Felix Hellmann <privat@cirk2.de>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: Lesaun Harvey <Lesaun@gmail.com>
Small, non-functional changes were made to non-compliant files.
These include breaking up long lines, whitespace sanitation and
unused import removal.
Maximum line length in python files was set to a generous 125 chars,
in order to minimize number of changes needed in scripts and general
annoyance. The "txt" prompts directory is excluded from the checks
as it may contain oddly formatted files and strings for a good reason.
Signed-off-by: Jiri Podivin <jpodivin@gmail.com>
