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RichardErkhov/CrabfishAI_-_InstructWise2-248M-awq
CrabfishAI_-_InstructWise2-248M-awq is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
22
52% of all-time downloads
All-time downloads
42
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248M
226 MB on disk
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Public
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.safetensors226 MB · 98%
How the weights are stored.
I32182M · 74%
From the Hugging Face model README
Quantization made by Richard Erkhov.
InstructWise2-248M - AWQ
tags:
autotrain
text-generation base_model: Locutusque/TinyMistral-248M datasets:
CrabfishAI/ReasoningQuestions
OpenAssistant/oasst_top1_2023-08-25
nRuaif/OpenOrca-GPT3.5 widget:
text: |- <|im_start|>user Find me a list of some nice places to visit around the world.<|im_end|>
<|im_start|>assistant
text: |- <|im_start|>user Tell me a story about some magical place.<|im_end|>
<|im_start|>assistant
text: |- <|im_start|>user Write a python code to print numbers from 1 to 100 in sequence.<|im_end|>
<|im_start|>assistant
text: |- <|im_start|>user What is biology?<|im_end|>
<|im_start|>assistant
text: >- <|im_start|>user I love taking photos of nature. Can you come up with a 3-day itinerary visiting the most photogenic places in Iceland?<|im_end|>
<|im_start|>assistant inference: parameters: max_new_tokens: 32 repetition_penalty: 1.15 do_sample: true temperature: 0.5 top_p: 0.5 license: apache-2.0 language:
en
Note- we,ll be releasing more versions of InstructWise soon, with the goal of making memory-efficent models while maintaining the performance, Thank you!
Introduction- InstructWise is a series of model created to act as helpful virtual assistant while maintaing the memory efficiency.
InstructWise finds application in various domains, including:
InstructWise can be directly employed for:
Educational Support:
Content Creation:
Code Assistance:
Interactive Conversations:
Q&A Platforms:
Technical Writing Support:
Idea Expansion:
Content Quality: The model's output may vary in quality, and there's a possibility it might generate content that is nonsensical, irrelevant, or grammatically incorrect.
Bias and Sensitivity: The model is trained on diverse data, but it may inadvertently exhibit biases or generate content that is sensitive or inappropriate. Exercise caution and review generated text before use.
Inappropriate Language: The model might generate text that includes offensive language or inappropriate content. Be mindful of this, especially in applications where maintaining a respectful and inclusive tone is essential.
Use with Caution: This model is a tool that should be used with caution. Always review and validate the generated text before incorporating it into any application or publication.
Not for Critical Applications: Avoid using the model for critical applications where accuracy and reliability are paramount. The model is intended for creative and exploratory purposes.
Ongoing Improvement: The model may be updated or fine-tuned for better performance. Stay informed about updates and consider using the latest version for improved results.
<|im_start|>user
[Your prompt here]<|im_end|>
<|im_start|>assistant