b1827 #71
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b1827 #71
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Uses ggml functions instead of hardcoded names and adds support to quantize into the modern Q-K variants. This is just the bare minimum to get k-types working - a more refined choice of types would be needed to get best quality on low quantizations. I ran a few tests, it doesn't break anything I could notice and a Q6_K ViT works almost as well as Q8_0 but 3 times the inference speed.
This update categorizes models with 24 layers as MODEL_1B, ensuring compatibility with different Phi model variants without impacting existing Phi-2 model functionality.
* llm_load_print_meta: Add additional suffixs for model params * Update llama.cpp model param log remove unneeded comments and convert from > to >=
* added /health endpoint to the server * added comments on the additional /health endpoint * Better handling of server state When the model is being loaded, the server state is `LOADING_MODEL`. If model-loading fails, the server state becomes `ERROR`, otherwise it becomes `READY`. The `/health` endpoint provides more granular messages now according to the server_state value. * initialized server_state * fixed a typo * starting http server before initializing the model * Update server.cpp * Update server.cpp * fixes * fixes * fixes * made ServerState atomic and turned two-line spaces into one-line
* added /health endpoint to the server * added comments on the additional /health endpoint * Better handling of server state When the model is being loaded, the server state is `LOADING_MODEL`. If model-loading fails, the server state becomes `ERROR`, otherwise it becomes `READY`. The `/health` endpoint provides more granular messages now according to the server_state value. * initialized server_state * fixed a typo * starting http server before initializing the model * Update server.cpp * Update server.cpp * fixes * fixes * fixes * made ServerState atomic and turned two-line spaces into one-line * updated `server` readme to document the `/health` endpoint too
* fix : cuda order of synchronization when setting a buffer * also sync before memcpy --------- Co-authored-by: slaren <[email protected]>
NULL can be an integer constant expression with the value zero, in this case the behavior would be undefined because of an incorrect type being passed to the variable arguments.
* change GGML_MAX_NAME to 128 * allow controlling the value of GGML_MAX_NAME through external macro definitions
* Token count changes * Add show token count * Updating before PR * Two requested changes * Move param def posn
* ci: nix-flake-update: new token with pr permissions --------- Co-authored-by: Georgi Gerganov <[email protected]>
* added /health endpoint to the server * added comments on the additional /health endpoint * Better handling of server state When the model is being loaded, the server state is `LOADING_MODEL`. If model-loading fails, the server state becomes `ERROR`, otherwise it becomes `READY`. The `/health` endpoint provides more granular messages now according to the server_state value. * initialized server_state * fixed a typo * starting http server before initializing the model * Update server.cpp * Update server.cpp * fixes * fixes * fixes * made ServerState atomic and turned two-line spaces into one-line * updated `server` readme to document the `/health` endpoint too * used LOG_INFO after successful model loading
* server: added support for multiple api keys, added loading api keys from file * minor: fix whitespace * added file error handling to --api-key-file, changed code to better reflect current style * server: update README.md for --api-key-file --------- Co-authored-by: Michael Coppola <[email protected]>
* Implement credentialed CORS according to MDN * Fix syntax error * Move validate_api_key up so it is defined before its first usage
* iq2_xs: basics * iq2_xs: this should have been in the basics * iq2_xs: CUDA and scalar CPU works * iq2_xs: WIP Metal * iq2_xs: Metal now works * iq2_xs: working, but dog slow, ARM_NEON dot product * iq2_xs: better ARM_NEON dot product We are now at 19.5 t/s for TG-128 and 61 t/s for PP-512 when running on the CPU. * iq2_xs: AVX2 dot product - 19.5 t/s * iq2_xs: faster AVX2 dit product 21.4 t/s for TG-128, 59.2 t/s for PP-512. The latter is 2x compared to the previous version. * iq2_xs: had forgotten to delete iq2-data.h * Add llama enum for IQ2_XS --------- Co-authored-by: Iwan Kawrakow <[email protected]>
* Restore intended k-quants quantization mixes for MoE models * Update Q2_K_S values in the quantize tool Still using LLaMA-v1 PPL values in the quant description today does not make much sense. But let's leave this update for another PR. --------- Co-authored-by: Iwan Kawrakow <[email protected]> Co-authored-by: Georgi Gerganov <[email protected]>
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Co-authored-by: Iwan Kawrakow <[email protected]>
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