transfer-learning-conv-ai | 🦄 State-of-the-Art Conversational AI with Transfer | Chat library

 by   huggingface Python Version: Current License: MIT

kandi X-RAY | transfer-learning-conv-ai Summary

kandi X-RAY | transfer-learning-conv-ai Summary

transfer-learning-conv-ai is a Python library typically used in Institutions, Learning, Education, Messaging, Chat, Deep Learning, Pytorch, Tensorflow applications. transfer-learning-conv-ai has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

State-of-the-Art Conversational AI with Transfer Learning
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            kandi-support Support

              transfer-learning-conv-ai has a medium active ecosystem.
              It has 1644 star(s) with 418 fork(s). There are 81 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 62 open issues and 47 have been closed. On average issues are closed in 83 days. There are 8 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of transfer-learning-conv-ai is current.

            kandi-Quality Quality

              transfer-learning-conv-ai has 0 bugs and 0 code smells.

            kandi-Security Security

              transfer-learning-conv-ai has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              transfer-learning-conv-ai code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              transfer-learning-conv-ai is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              transfer-learning-conv-ai releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              transfer-learning-conv-ai saves you 278 person hours of effort in developing the same functionality from scratch.
              It has 673 lines of code, 27 functions and 6 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed transfer-learning-conv-ai and discovered the below as its top functions. This is intended to give you an instant insight into transfer-learning-conv-ai implemented functionality, and help decide if they suit your requirements.
            • Start training
            • Run the command
            • Get data loaders
            • Filtering logits with a given threshold
            • Generate a sequence of tokens
            • Get a dataset
            • Build a input from a list of tokens
            • Download pretrained pretrained model
            • Create logdir for a model
            • Adds special tokens to the model
            • Pad a dataset
            • Observe an observation
            • Reset the profile
            • Run the script
            • Actual actions
            • Compute the probability of the next word
            Get all kandi verified functions for this library.

            transfer-learning-conv-ai Key Features

            No Key Features are available at this moment for transfer-learning-conv-ai.

            transfer-learning-conv-ai Examples and Code Snippets

            NeuralPipeline_DSTC8,How to train
            Pythondot img1Lines of Code : 6dot img1no licencesLicense : No License
            copy iconCopy
            cd ConvLab # (working directory)
            cd data/multiwoz
            unzip total_v4.zip
            unzip val_v4.zip
            cd ../../  # (working directory)
            python -m torch.distributed.launch --nproc_per_node=${#OfGPUs, e.g.2} convlab/modules/e2e/multiwoz/Transformer/train.py --dataset_p  

            Community Discussions

            Trending Discussions on transfer-learning-conv-ai

            QUESTION

            No module named 'numpy' during docker build
            Asked 2021-May-27 at 16:31

            I am following the instruction (https://github.com/huggingface/transfer-learning-conv-ai) to install conv-ai from huggingface, but I got stuck on the docker build step: docker build -t convai .

            I am using Mac 10.15, python 3.8, increased Docker memory to 4G.

            I have tried the following ways to solve the issue:

            1. add numpy in requirements.txt
            2. add RUN pip3 install --upgrade setuptools in Dockerfile
            3. add --upgrade to RUN pip3 install -r /tmp/requirements.txt in Dockerfile
            4. add RUN pip3 install numpy before RUN pip3 install -r /tmp/requirements.txt in Dockerfile
            5. add RUN apt-get install python3-numpy before RUN pip3 install -r /tmp/requirements.txt in Dockerfile
            6. using python 3.6.13 because of this post, but it has exact same error.
            7. I am currently working on debugging inside the container by entering right before the RUN pip3 install requirements.txt

            Can anyone help me on this? Thank you!!

            The error:

            ...

            ANSWER

            Answered 2021-Mar-12 at 15:47

            Did you try adding numpy into the requirements.txt? It looks to me that it is missing.

            Source https://stackoverflow.com/questions/66602656

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install transfer-learning-conv-ai

            To install and use the training and inference scripts please clone the repo and install the requirements:.
            To install using docker please build the self-contained image:. You can then enter the image.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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          • HTTPS

            https://github.com/huggingface/transfer-learning-conv-ai.git

          • CLI

            gh repo clone huggingface/transfer-learning-conv-ai

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            git@github.com:huggingface/transfer-learning-conv-ai.git

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