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* Use named tuple from typing for typehints * Add type hints * Simplify expression * Type hint fix * Improved do_POST logic Use a map of endpoints to methods to reduce redundancy in code * Fix format * Improve redundancy Call method dynamically instead of writing out all arguments twice * Send response instead of returning * Fix typo * Revert change * Make adapter_file as Optional * Mark formatter as optional * format * Create message generator Store response data that stays static for the duration of the response inside of the object: system_fingerprint request_id object_type requested_model Created a message generator, that dynamically creates messages from the metadata stored inside of the object, and the data from the model pipeline * Remove leftover * Update parameters to reflect new object structure No longer pass all arguments between functions, but use the stores values inside of the object * Parse body before calling request specific methods * Call super init * Update server.py * Fixed outdated documentation parameter name * Add documentation * Fix sending headers twice During testing I found that when using the streaming option, headers have always been sent twice. This should fix that * Simplify streaming code by using guard clauses Don't wrap wfile writes in try blocks, the server class has its own try block to prevent crashing * Bug fix * Use Content-Length header Let the completion type specific methods finish sending the headers. This allows us to send the Content-Length header as the model returns a completion. * Update utils.py * Add top_p documentation * Type hint model and tokenizer as required * Use static system fingerprint System fingerprint now stays the same across requests * Make type hint more specific * Bug Fix Supplying less than 2 models to merge would raise ValueError and calls len on unbound "models". Should be "model_paths" instead. Mark upload_repo as optional * Move more of the shared code into do_POST Processing stop_id_sequences is done no matter the request endpoint or type, move it into the shared section. handle_ methods now just return the prompt in mx.array form. * Store stop_id_sequences as lists instead of np During testing I found that letting the tokenizer return values as python lists and converting them to mlx arrays was around 20% faster than having the tokenizer convert them to np, and from np to mlx. This allows makes it so numpy no longer needs to be imported. * Update stop_id_sequences docs * Turn if check to non-inclusive Only continue if buffer is smaller * Documentation fix * Cleared method names Instead of handle_stream and generate_competion, we should name it handle_completion. Instead of handle_completions and handle_chat_completions, we should name it handle_text_completions, since both are completions, calling it text completions should make it more descriptive * Make comment clearer * fix format * format
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601 B
Markdown
16 lines
601 B
Markdown
# Individual Contributors
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If you wish to be acknowledged for your contributions, please list your name
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with a short description of your contribution(s) below. For example:
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- Jane Smith: Added the `foo` example.
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MLX Examples was developed with contributions from the following individuals:
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- Juarez Bochi: Added support for T5 models.
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- Sarthak Yadav: Added the `cifar` and `speechcommands` examples.
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- Shunta Saito: Added support for PLaMo models.
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- Gabrijel Boduljak: Implemented `CLIP`.
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- Markus Enzweiler: Added the `cvae` examples.
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- Prince Canuma: Helped add support for `Starcoder2` models.
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