I have trained 3 different NER model on existing model in spacy version 3. i want to combine those three models to a single pipeline in spacy, so i can load the three of them as one model. Can someone please help me on this.Spacy version 3 details are very less can someone please help me.
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I am using Rasa NLU. I have 3 models trained using the same pipeline with different training datasets. The pipeline uses Spacy for tokenization and to build the WordVec.
When I load all of those 3 models to memory, Exactly how many times, Rasa loads Spacy en_core_web_lg model to the memory? Can we share the same Spacy model between multiple trained NLU models?
The Spacy model will be loaded into memory each time you train a model using it. It will however only be downloaded once, in which sense the same model is used for all NLU models trained in the same environment.
This question is of a more conceptual type.
I was using the pre-trained word-vectors of spacy (the de_core_news_md model).
The problem is that I have a lot of domain specific words which all get a 0-vector assignet and overall the results are in gerneral not too good.
I was wondering how one should proceed now.
should I try to fine tune the existing vectors? If so, how would one approach that?
Or, should I just not use the pre-trained word vectors of spacy and create my own?
Edit:
I want to fine tune the pre trained vectors. I've read, that I could train the already trained model again but on my data. Now my question is, how to do that. When I use spacy, i just load the model. Should I download the vectors of spacy and train a gensim model with them and afterwards again with my vectors? Or is there a better way?
Thank you in advance for any input!
I am new to the Transformers concept and I am going through some tutorials and writing my own code to understand the Squad 2.0 dataset Question Answering using the transformer models. In the hugging face website, I came across 2 different links
https://huggingface.co/models
https://huggingface.co/transformers/pretrained_models.html
I want to know the difference between these 2 websites. Does one link have just a pre-trained model and the other have a pre-trained and fine-tuned model?
Now if I want to use, let's say an Albert Model For Question Answering and train with my Squad 2.0 training dataset on that and evaluate the model, to which of the link should I further?
I would formulate it like this:
The second link basically describes "community-accepted models", i.e., models that serve as the basis for the implemented Huggingface classes, like BERT, RoBERTa, etc., and some related models that have a high aceptance or have been peer-reviewed.
This list has bin around much longer, whereas the list in the first link only recently got introduced directly on the Huggingface website, where the community can basically upload arbitrary checkpoints that are simply considered "compatible" with the library. Oftentimes, these are additional models trained by practitioners or other volunteers, and have a task-specific fine-tuning. Note that al models from /pretrained_models.html are also included in the /models interface as well.
If you have a very narrow usecase, you might as well check and see if there was already some model that has been fine-tuned on your specific task. In the worst case, you'll simply end up with the base model anyways.
I am starting to work with Intel movidius neural compute stick.
To start working, in my case, it is necessary to download pretrained models.
In the tutorials they refer to http://download.tensorflow.org/models/.
However, there is not a list that shows all the models available for download.
If the latest version of a net, lets say inception_v4, is not known, I cannot download the corresponding .tar.gz file.
Does anyone know a method to have an updated list of the .tar.gz files of the pretrained models available for download?
Thanks
The following two links may help
detection_model_zoo
TensorFlow-Slim image classification model library
keras.applications makes it easy to load models and their pretrained weights if you can use Keras
Considering that most of the posted linked outdated, I suggest looking into the TensorFlow hub (https://www.tensorflow.org/hub) for more recent pre-trained models.
I'm using tensorflow to train inception v3, and I get two different output files, the one is output_graph.pb and the other saved_model.pb. I checked some pages about the difference between them, but I didn't really get it. Is there any one who can explain it to me? Thanks a lot.