GitHub – simonw/language-models-on-the-command-line: Handout for a talk I gave about LLM and CLI tools https://
bit.ly/3Wgpg8p
#AI #MachineLearning #DeepLearning #LLMs #DataScience
OPEN SOURCE
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Language Models on Command Line: CLI Integration Guide
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CogVideoX: High Quality Text to Video Generation
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CogVideoX
— AK (@_akhaliq) 5 août 2024
high quality text to video generationhttps://t.co/7tOM5KU3Ww pic.twitter.com/tInxbQg8fzCogVideoX high quality text to video generation https://
huggingface.co/spaces/THUDM/C
ogVideoX
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Llama Impact Grant Program Expands with Global Events and Support
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The Llama Impact Grant program is growing
This year we're expanding the Llama Impacts Grant program by hosting a series of virtual events and in-person hackathons, workshops and trainings around the world — and providing technical guidance and mentorship to prospective -
Llama 3.1 Impact Grants Support Global Community Projects
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We’re inspired by the diverse projects we’ve seen developers undertake around the world to positively impact their communities by building with Llama and we're excited to support a new wave of global community impact with the Llama 3.1 Impact Grants.
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Llama 3.1 Compatibility and Overlap with Previous Version
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Yes, there seems to be a large overlap. Llama 3.1 is based on 3.0, so it's not too crazy but it's nice it works without requiring any tweaking
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Llama 3.1 70B Recipe Adapted with LoRA Optimization
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I adapted this recipe to Llama 3.1 70B using @failspy
's Meta-Llama-3-70B-Instruct-abliterated-v3.5 and optimized the LoRA rank. GGUF quants are ready and there shouldn't be any issue with the tokenizer. Special thanks to him and to grimjim for the model and this technique. -
Uncensored Llama 3.1 70B Instruct Model Released
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Llama 3.1 70B Instruct lorablated It's an uncensored Llama 3.1 70B Instruct using grimjim's recipe of LoRA + abliteration (lorablation). The model is fully uncensored in my tests and maintains a high level of quality. Model: https://
huggingface.co/mlabonne/Llama
-3.1-70B-Instruct-lorablated
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Lorablation: Two-Step LoRA Extraction for Model Abliteration
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Lorablation is a simple two-step process: 1/ Extract a LoRA by comparing two models: a censored and an abliterated Llama 3.0 2/ Merge the LoRA with a censored Llama 3.1 to abliterate it It means that we directly applied a Llama 3 LoRA to a 3.1 model and it just works!
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htmx2ft adds flexible syntax output support
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Ah what the hell here's another quick release to add a last minute PR. `htmx2ft` now supports either children-first or attr-first syntax output. https://
github.com/AnswerDotAI/fa
sthtml/pull/193
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htmx2ft releases children-first and attr-first syntax output
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Ah what the hell here's another quick release to add a last minute PR. `htmx2ft` now supports either children-first or attr-first syntax output.