The default values for tfs_z and typical_p were being set to zero, which
caused the token candidates array to get shrunk down to one element thus
preventing any sampling. Note this only applies to OpenAI API compatible
HTTP server requests.
The solution is to use the default values that OpenAI documents, as well
as ensuring we use the llama.cpp defaults for the rest. I've tested this
change still ensures deterministic output by default. If a "temperature"
greater than 0 is explicitly passed, then output is unique each time. If
"seed" is specified in addition to "temperature" then the output becomes
deterministic once more.
See mozilla-Ocho/llamafile#117
See mozilla-Ocho/llamafile@9e4bf29
* cuda : fix vmm pool with multi GPU
* hip
* use recommended granularity instead of minimum
* better error checking
* fix mixtral
* use cudaMemcpy3DPeerAsync
* use cuda_pool_alloc in ggml_cuda_op_mul_mat
* consolidate error checking in ggml_cuda_set_device
* remove unnecessary inlines
ggml-ci
* style fixes
* only use vmm for the main device
* fix scratch buffer size, re-enable vmm pool for all devices
* remove unnecessary check id != g_main_device
* Add logit_bias to the OpenAI api
* Cleanup and refactor, test in swagger.
---------
Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com>
* Downgrade CUDA to 11.4
This helps the binary be smaller and adds K80 support, the manual compiles we did already had this.
* Update kcpp-build-release-win-cuda.yaml
* Update kcpp-build-release-win-cuda.yaml
* Update kcpp-build-release-win-cuda.yaml
* Update kcpp-build-release-win-cuda.yaml
* Update kcpp-build-release-win-cuda.yaml
* Update kcpp-build-release-win-cuda.yaml
* Restore concedo_experimental
* cuda : improve cuda pool efficiency using virtual memory
* fix mixtral
* fix cmake build
* check for vmm support, disable for hip
ggml-ci
* fix hip build
* clarify granularity
* move all caps to g_device_caps
* refactor error checking
* add cuda_pool_alloc, refactor most pool allocations
ggml-ci
* fix hip build
* CUBLAS_TF32_TENSOR_OP_MATH is not a macro
* more hip crap
* llama : fix msvc warnings
* ggml : fix msvc warnings
* minor
* minor
* cuda : fallback to CPU on host buffer alloc fail
* Update ggml-cuda.cu
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Update ggml-cuda.cu
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* ensure allocations are always aligned
* act_size -> actual_size
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Check the full vocab for grammar only if necessary
* Fix missing logit restoration step (?)
Does this matter, actually?
* Fix whitespace / formatting
* Adjust comment
* Didn't mean to push test gbnf
* Split sampling into the helper function (?)
And also revert the changes made to the header
* common : fix final newline
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* initial commit, going through initializations
* main loop finished, starting to debug
* BUG: generates gibberish/repeating tokens after a while
* kv_cache management
* Added colors to distinguish drafted tokens (--color). Updated README
* lookup : fix token positions in the draft batch
* lookup : use n_draft from CLI params
* lookup : final touches
---------
Co-authored-by: Leon Ericsson <leon.ericsson@icloud.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* fix old jetson compile error
* Update Makefile
* update jetson detect and cuda version detect
* update cuda marco define
* update makefile and cuda,fix some issue
* Update README.md
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Update Makefile
* Update README.md
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
