DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters
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DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters
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*** Happy Halloween - Embrace the Horror ! ***
Unsloth fine tunes using in house horror dataset.
Gemma 3 - 1B, 4B, two 12Bs and 27B (uploaded yesterday)
Qwen 3 - 1.7B [two] - new today... and , 4B, 6B, 42B ...
And 32 MORE horror models:
https://huggingface.co/DavidAU/models?search=horror
Collection:
https://huggingface.co/collections/DavidAU/grand-horror-165b-horror-and-fiction-generation
Enjoy ;
Unsloth fine tunes using in house horror dataset.
Gemma 3 - 1B, 4B, two 12Bs and 27B (uploaded yesterday)
Qwen 3 - 1.7B [two] - new today... and , 4B, 6B, 42B ...
And 32 MORE horror models:
https://huggingface.co/DavidAU/models?search=horror
Collection:
https://huggingface.co/collections/DavidAU/grand-horror-165b-horror-and-fiction-generation
Enjoy ;
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#23 opened 7 months ago
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Dampfinchen
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2017
I've recently attended a panel on AI applications. The panelists are managers/directors of Fortune 500 companies. These people make things happen and own results, so their stories and pain points are fresh.
(1) Models are used EVERYWHERE, customer facing and internal support, etc.
(2) A successful application must improve one of the following: revenue (💵💵), cost (💵💵), CSAT (still 💵💵)
(3) They proactively search on 🤗HF🤗 for models and use them. Open source models (especially small ones) can flexibly fit into their existing workflows/infras, which enable them to deliver, and fast.
(4) The main barrier for adoption is license. A director told me they picked a model and finetuned it, then learned they would have to share enhancements. As a result, they dropped this model and the million dollar impact went to another model.
So to fellow model builders:
(1) celebrate that our work is useful and generate lots of values
(2) make your license permissive if you want maximum impact
(1) Models are used EVERYWHERE, customer facing and internal support, etc.
(2) A successful application must improve one of the following: revenue (💵💵), cost (💵💵), CSAT (still 💵💵)
(3) They proactively search on 🤗HF🤗 for models and use them. Open source models (especially small ones) can flexibly fit into their existing workflows/infras, which enable them to deliver, and fast.
(4) The main barrier for adoption is license. A director told me they picked a model and finetuned it, then learned they would have to share enhancements. As a result, they dropped this model and the million dollar impact went to another model.
So to fellow model builders:
(1) celebrate that our work is useful and generate lots of values
(2) make your license permissive if you want maximum impact
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Let's Give Credit Where It’s Due: Adding Source Links to AI Responses
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#88 opened 10 months ago
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Munis01
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10 months ago
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5200
Deepswipe by
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. Deepseek🐬🗿
Everything is now in recovery. 📉📈
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. Deepseek🐬🗿
Everything is now in recovery. 📉📈
- 4 replies