* make buffer view optional with a flag [run_process_replay]
* do not view when sharding to save memory [run_process_replay]
* llama shard axis=0 sometimes
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
Co-authored-by: chenyu <chenyu@fastmail.com>
copy scale on all device for now. naive sharding does not work because scale needs expand to really save memory.
70B does not work due to HSA_STATUS_ERROR_OUT_OF_RESOURCES.
`python3 examples/llama.py --gen 2 --size 13B --shard 6 --prompt "Hello." --count 10 --temperature 0 --timing --quantize`
13B on 6 gpus uses 47 GB v.s. 34 GB quantized
* shard llama
* sharding works
* simpler
* simpler
* consume option
* disable that test
* save a line
---------
Co-authored-by: George Hotz <george@tinygrad.org>
* feat: working voice 2 text using whisper
* feat: added llama generation
* feat: vits init
* feat: more accurate voice conversion
* feat: support for tts and working pipeline for the first pass
* fix: linter checks
* refactored vits initialization and inference, added mmts-tts support
* fixed process sync and now we can have an infinite conversation
* reuse output stream to remove overhead of creating a new one each time
* added pre-prompt configuration with yaml files
* adjusted code to merge PR which changed whisper
* optimized whisper, now it's blazing fast and also reduced number of lines
* added better debug printing
* use jitted encode function for whisper, added timings and removed response delim to save speed on generating those tokens
* fixed hf convert and now it's working with tinyllama
* added tinyllama config
* refactored code and made it work with all llama models
* prettier order
* prettier order
* fixed suffix for tinyllama and refactored convert_from_hf
* added missing parameters
* fixed stream release and added missing params
* jitted dp and encoder
* jitted flow forward
* removed re-init of espeak on each call to save up time
* jitted generator forward for blazing fast tts
* added contextmanager for displaying a chat log
* removed whitespace for pylint
* updated code to support latest fetch func
* wait for llama eos token and pass params from cli to llama
* listen for not fixed amount of time
* refactored code a bit
* removed thresholding and now the output streams directly to whisper
* tokenize llama output for vits batch size to work and stream each sentence to a speaker
* changed speaker
* whisper is now printing on the same line
* don't trigger llama on whisper output in parens
* added tinyllama chat model
* adjusted code to work with tinyllama chat model
* removed unused cli arg
* autofetch tokenizer and tinyllama model. add 3 chat tokens to the tokenizer
* fixed issue with long sentences by chunking them
* support for multiline llama output
* prettified log output
* adjusted sentence length
* remove quote from response to avoid funny tts
* fixed prompts
* added missing parameter
* fixed hf convert and now it's working with tinyllama
* added tinyllama config
* refactored code and made it work with all llama models
* prettier order
* prettier order
* fixed suffix for tinyllama and refactored convert_from_hf
* dynamically update help if MODEL_PARAMS changes and default size is the 1st
