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NeuralChat.yaml
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---
# Thank you for contributing!
# In filling out this yaml file, please follow the criteria as described here:
# https://github.com/opening-up-chatgpt/opening-up-chatgpt.github.io/tree/main/projects#criteria
# You're free to build on this work and reuse the data. It is licensed under CC-BY 4.0, with the
# stipulation that attribution should come in the form of a link to http://opening-up-chatgpt.github.io
# and a citation to the paper in which the initial dataset & criteria were published:
# Liesenfeld, Andreas, Alianda Lopez, and Mark Dingemanse. 2023. “Opening up ChatGPT: Tracking Openness, Transparency, and Accountability in Instruction-Tuned Text Generators.” In CUI '23: Proceedings of the 5th International Conference on Conversational User Interfaces. July 19-21, Eindhoven. doi: 10.1145/3571884.3604316
system:
name: NeuralChat
link: https://huggingface.co/Intel/neural-chat-7b-v3-3
type: text
performanceclass: full
basemodelname: Mistral-7B-v0.1
endmodelname: Neural-Chat-7B-v3.3
endmodellicense: Apache 2.0
releasedate: 2023-11
notes: New model. TODO update fields. A mistral-based Orca-finetuned chat model
org:
name: Intel
link: https://community.intel.com/t5/Blogs/Tech-Innovation/Artificial-Intelligence-AI/NeuralChat-A-Customizable-Chatbot-Framework/post/1526789
notes:
# availability:
datasources_basemodel:
class: closed
link:
notes: Mistral has not disclosed anything about its training data
datasources_endmodel:
class: open
link: https://huggingface.co/datasets/Open-Orca/SlimOrca
notes: RL dataset used for post-training is shared and available
weights_basemodel:
class: open
link: https://huggingface.co/mistralai/Mistral-7B-v0.1
notes: Based on Mistral 7B 0.1
weights_endmodel:
class: open
link: https://huggingface.co/Intel/neural-chat-7b-v3-1/tree/main
notes: finetuned model made openly available by Intel
trainingcode:
class: partial
link: https://github.com/intel/intel-extension-for-transformers/tree/main/intel_extension_for_transformers/neural_chat/examples/finetuning/finetune_neuralchat_v3
notes: Mistral base model is not open, but repo gives sample code for fine-tuning based on that
# documentation:
code:
class: partial
link: https://github.com/intel/intel-extension-for-transformers/tree/main/intel_extension_for_transformers/neural_chat/examples/finetuning/finetune_neuralchat_v3#how-to-train-intelneural-chat-7b-v3-1-on-intel-gaudi2
notes: Mistral remains closed so only documentation pertains to fine-tuning steps, but that code is quite well documented, so partial.
architecture:
class: partial
link: https://medium.com/intel-analytics-software/the-practice-of-supervised-finetuning-and-direct-preference-optimization-on-habana-gaudi2-a1197d8a3cd3
notes: Described on HuggingFace model card and a Medium post
preprint:
class: closed
link: https://medium.com/intel-analytics-software/the-practice-of-supervised-finetuning-and-direct-preference-optimization-on-habana-gaudi2-a1197d8a3cd3
notes: A medium post is apparently the only scientific documentation of this model
paper:
class: closed
link:
notes: No peer-reviewed paper found
modelcard:
class: partial
link: https://huggingface.co/Intel/neural-chat-7b-v3-1
notes: No model card for Mistral base model portion.
datasheet:
class: partial
link: https://huggingface.co/datasets/Open-Orca/OpenOrca
notes: SlimOrca dataset is described as part of OpenOrca (but partial since Mistral data is incrutable)
# access:
package:
class: partial
link: https://huggingface.co/Intel/neural-chat-7b-v3-1#fp32-inference-with-transformers
notes: Code for running with transformers provided by Intel
api:
class: closed
link:
notes: Provided through HuggingFace but model too large to run via inference API, local deployment or paid access needed
metaprompt: closed
licenses:
class: open
link: https://huggingface.co/Intel/neural-chat-7b-v3-1/blob/main/LICENSE
notes: Apache 2.0