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2023-12-06common : fix compile warningGeorgi Gerganov
2023-12-05sampling : custom samplers order (#4285)MaggotHATE
* Samplers sequence order w parameter * Cleaned commented code * Fixed formatting * Rewrote with unordered_map * Revert and rewrite, too many problems and safeguards would be needed * Fixed code style * Code style fixes according to review * More readable samplers input string, fixed help * Style fix in sampler_queue * Formatting fixes * Fixing whitespaces
2023-11-01sampling : null grammar field after reset (#3885)l3utterfly
2023-10-31samplers : Min-P sampler implementation [alternative to Top P/Top K] (#3841)kalomaze
* Introduce the new Min-P sampler by @kalomaze The Min-P sampling method was designed as an alternative to Top-P, and aims to ensure a balance of quality and variety. The parameter *p* represents the minimum probability for a token to be considered, relative to the probability of the most likely token. * Min-P enabled and set to 0.05 default --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: cebtenzzre <cebtenzzre@gmail.com>
2023-10-28llama : add option for greedy sampling with probs (#3813)Georgi Gerganov
* llama : add option for greedy sampling with probs * llama : add comment about llama_sample_token_greedy() missing probs * sampling : temp == 0.0 -> no probs, temp < 0.0 -> probs
2023-10-23llama : remove token functions with `context` args in favor of `model` (#3720)Marcus Dunn
* added `llama_model_token_*` variants to all the `llama_token_*` functions. * added `LLAMA_API` * formatting Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * removed old `llama_token` functions * changed 3 more functions to take in model - `llama_token_get_text` - `llama_token_get_score` - `llama_token_get_type` * added back docs * fixed main.cpp * changed token functions to use new model variants * changed token functions to use new model variants --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-10-20sampling : refactor init to use llama_sampling_params (#3696)Georgi Gerganov
* sampling : refactor init to use llama_sampling_params * llama : combine repetition, frequency and presence penalties in 1 call * examples : remove embd-input and gptneox-wip * sampling : rename penalty params + reduce size of "prev" vector * sampling : add llama_sampling_print helper * sampling : hide prev behind API and apply #3661 ggml-ci
2023-10-18speculative : add tree-based sampling example (#3624)Georgi Gerganov
* sampling : one sequence per sampling context ggml-ci * speculative : add tree-based sampling support ggml-ci * speculative : reuse the n_parallel CLI param * speculative : refactor sampling * examples : fix build after sampling refactoring ggml-ci * batched : fix n_seq_id * sampling : fix malloc ggml-ci * swift : fix build ggml-ci * swift : try to fix build ggml-ci * prompts : add assistant.txt * common : add llama_batch_add() and llama_batch_clear() helpers * speculative : minor refactor ggml-ci * minor : comments + rename ggml-ci * speculative : fix off-by-one for n_drafted * speculative : fix the n_drafted fix + p constants
2023-10-11common : fix mirostat state when using multiple sequences (#3543)Kerfuffle
* Fix mirostat state when using multiple sequences * Fix mirostat by completely refactoring sampling! * Try to fix zig build. * Export function to fetch/create default sampler states Code formatting cleanups and add some comments Silence a warning about id not being used when logging is disabled * Apply some renaming suggestions. Fix comments that were out of sync with the pull. * Use more consistant naming convention for sampling contexts