marian | Fast Neural Machine Translation in C++ | Machine Learning library
kandi X-RAY | marian Summary
kandi X-RAY | marian Summary
[Twitter] Marian is an efficient Neural Machine Translation framework written in pure C++ with minimal dependencies. Named in honour of Marian Rejewski, a Polish mathematician and cryptologist.
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QUESTION
Hi I am beginner with web scraping. I am trying to scrape all the links from a website and I am successful to some extent.
...ANSWER
Answered 2021-May-14 at 15:05Try the following to get the links that do not starts with #. You can choose either of the conditions to meet the requirement:
QUESTION
I am working on assigning random priorities (i.e. high, medium, low) to a list for a ServiceDesk assignment.
Before that, I was wondering how to go about storing (and printing) an array in said priority queue. This is currently what I have.
*UPDATED CODE
...ANSWER
Answered 2021-Apr-18 at 02:33Sounds like you are asking for help on how to get started. You are asking for help on learning to learn. Here is how I would approach your problem:
Apparently you are supposed to use a priority queue.
- Write a tiny program that makes a priority queue and stores strings into it, then prints them out.
- Define a class and store instances of that class into the priority queue instead of strings.
- Modify the sort criteria on the priority queue and notice that the printed sequence changes according to the sort criteria.
- Write a function that creates one class instance with random values.
- Write a function that creates all 100 class instances.
- Declare victory.
QUESTION
Currently Helsinki-NLP/opus-mt-es-en model takes around 1.5sec for inference from transformer. How can that be reduced? Also when trying to convert it to onxx runtime getting this error:
ValueError: Unrecognized configuration class for this kind of AutoModel: AutoModel. Model type should be one of RetriBertConfig, MT5Config, T5Config, DistilBertConfig, AlbertConfig, CamembertConfig, XLMRobertaConfig, BartConfig, LongformerConfig, RobertaConfig, LayoutLMConfig, SqueezeBertConfig, BertConfig, OpenAIGPTConfig, GPT2Config, MobileBertConfig, TransfoXLConfig, XLNetConfig, FlaubertConfig, FSMTConfig, XLMConfig, CTRLConfig, ElectraConfig, ReformerConfig, FunnelConfig, LxmertConfig, BertGenerationConfig, DebertaConfig, DPRConfig, XLMProphetNetConfig, ProphetNetConfig, MPNetConfig, TapasConfig.
Is it possible to convert this to onxx runtime?
...ANSWER
Answered 2021-Jan-13 at 10:10The OPUS models are originally trained with Marian which is a highly optimized toolkit for machine translation written fully in C++. Unlike PyTorch, it does have the ambition to be a general deep learning toolkit, so it can focus on MT efficiency. The Marian configurations and instructions on how to download the models are at https://github.com/Helsinki-NLP/OPUS-MT.
The OPUS-MT models for Huggingface's Transformers are converted from the original Marian models are meant more for prototyping and analyzing the models rather than for using them for translation in a production-like setup.
Running the models in Marian will certainly much faster than in Python and it is certainly much easier than hacking Transformers to run with onxx runtime. Marian also offers further tricks to speed up the translation, e.g., by model quantization, which is however at the expense of the translation quality.
With both Marian and Tranformers, you can speed things up if you use GPU or if you narrow the beam width during decoding (attribute num_beams in the generate method in Transformers).
QUESTION
I am trying to implement a search for a user using his username, username fields are unique. The result is to be all users whose username contains the string. During the query, the 'q' parameter is correctly passed to the find () function, but when the 'q' parameter contains only a part of the username in the response, an empty array is returned. However, when the whole username is given, the answer is correct.
My users.controller function:
...ANSWER
Answered 2020-Nov-22 at 18:37Search does not work like that. It's probably more complicated than this, but it seems the only simple inferences are done.
"blue", it won't match blueberry; however, "blueberry" will match blueberries.
You can still create a standard index on the username, and then use regex, like so:
QUESTION
I have this code in my controller:
...ANSWER
Answered 2020-Oct-30 at 07:40I think you just have a mistype in your foreach
Try this
QUESTION
I am trying to save the tokenizer in huggingface so that I can load it later from a container where I don't need access to the internet.
...ANSWER
Answered 2020-Oct-28 at 09:27save_vocabulary(), saves only the vocabulary file of the tokenizer (List of BPE tokens).
To save the entire tokenizer, you should use save_pretrained()
Thus, as follows:
QUESTION
I have two collections:
Audios
...ANSWER
Answered 2020-Oct-03 at 11:05What you have tried was correct.
QUESTION
My problem is that I have a vector including comments and another vector including names which I am trying to find in the comments. My approach is using fuzzywuzzy and assigning in a first step each name the points it gets for the corresponding comment. So that I will be able to say which names were likely mentioned in which comment in a further step
For instance the data could look like that:
...ANSWER
Answered 2020-Oct-01 at 15:11The issue here isn't Python so much as DataFrames, which work similarly to SQL tables whether you're dealing with Pandas or PySpark: Whenever possible, you should vectorize operations on the DF. This lets the computer worry about parallelizing the algorithm.
If you have a pre-existing DF, you can efficiently apply a function to every element using pandas.DataFrame.apply().
In your case, it looks more like you're just looking for a better way to initialize the DF. If you can describe your DF contents as a list of dictionaries (with one dict per record), I recommend using pandas.DataFrame.from_records(). Each dict in the list will have a form like {'Comments': 'Ana Starkov was super good!', 'Anna Starkow': 80, 'Marian Mueller': 0} (The from_dict() method is similar in concept, but has a slightly different input format.)
This will be significantly faster than building / rewriting a DF cell-by-cell.
QUESTION
I need help to fix my code. as i failed the last one no 9.
Q: Fill in the if_then_elseif() function to create the desired array using a for loop and an if then else statement. The goal is to create an output table equivalent to the input table as per the following correspondence {"1", "2", "3", "4", "5", "6", "7", "8", "9"} =>> {"a", "b", "c", "d", "e", "f", "n", "n", "n"} ]]
...ANSWER
Answered 2020-Sep-27 at 15:17My personal recommendation:
QUESTION
In MS Project Professional I have a custom field that returns the correct value...sometimes, no value at other times, and an #ERROR at still other times with no apparent rhyme or reason.
The goal: I need to capture the [Resource Names] field for use in an external application - easy enough - but when I have a fixed units task with limited resource units I need to exclude the "[##%]" portion of the name. Example: Sam[25%] but I need just, "Sam"
The formula: IIf(IsNumeric(InStr(1,[Resource Names],"[")),LEFT([Resource Names],Len([Resource Names])-5),[Resource Names])
The results are in summary:
- Marian == M
- Sam == #ERROR
- Sam[25%] == Sam
- IDNR == #ERROR
- Core Dev == Cor
- Bindu == Bindu
- Bindu[50%] == Bindu
- Michele == Mi
- Michele[25%] == Michele
- Disha == empty
- Disha[33%] == Disha
- Stuart[50%] == Stuart
- Stuart == S
Strangely enough, Summary Tasks show no value which is correct.
The need: can someone help me fix the formula? Or, should I just suck it up and manually delete the offending brackets and numbers?
...ANSWER
Answered 2020-Sep-22 at 23:45If you only ever have one resource assigned to a task, this formula will work: IIf(0=InStr(1,[Resource Names],"["),[Resource Names],Left([Resource Names],InStr(1,[Resource Names],"[")-1)).
However, building a formula to handle more than one resource would be extremely tedious with the limited functions available. In that case a macro to update the field would work much better:
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