Post
5057
Deepswipe by
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. Deepseek🐬🗿
Everything is now in recovery. 📉📈
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. Deepseek🐬🗿
Everything is now in recovery. 📉📈
- 4 replies
Jae Hutchinson
sirmyrrh
AI & ML interests
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Recent Activity
new activity
7 days ago
deepseek-ai/DeepSeek-R1:Let's Give Credit Where It’s Due: Adding Source Links to AI Responses
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prithivMLmods's
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with 😎
8 days ago
Deepswipe by
.
.
.
. Deepseek🐬🗿
Everything is now in recovery. 📉📈
upvoted
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collection
9 days ago
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sirmyrrh's activity
Let's Give Credit Where It’s Due: Adding Source Links to AI Responses
3
#88 opened 8 days ago
by
Munis01
reacted to
prithivMLmods's
post with 😎
8 days ago
upvoted
a
collection
9 days ago
reacted to
mlabonne's
post with 🤗
22 days ago
Post
4131
🆕 LLM Course 2025 edition!
I updated the LLM Scientist roadmap and added a ton of new information and references. It covers training, datasets, evaluation, quantization, and new trends like test-time compute scaling.
The LLM Course has been incredibly popular (41.3k stars!) and I've been touched to receive many, many messages about how it helped people in their careers.
I know how difficult this stuff can be, so I'm super proud of the impact it had. I want to keep updating it in 2025, especially with the LLM Engineer roadmap.
Thanks everyone, hope you'll enjoy it!
💻 LLM Course: https://huggingface.co/blog/mlabonne/llm-course
I updated the LLM Scientist roadmap and added a ton of new information and references. It covers training, datasets, evaluation, quantization, and new trends like test-time compute scaling.
The LLM Course has been incredibly popular (41.3k stars!) and I've been touched to receive many, many messages about how it helped people in their careers.
I know how difficult this stuff can be, so I'm super proud of the impact it had. I want to keep updating it in 2025, especially with the LLM Engineer roadmap.
Thanks everyone, hope you'll enjoy it!
💻 LLM Course: https://huggingface.co/blog/mlabonne/llm-course
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Magnum v4
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#4 opened about 2 months ago
by
EloyOn
https://huggingface.co/rhplus0831/maid-yuzu-v8-alter
9
#482 opened 2 months ago
by
sirmyrrh
upvoted
2
collections
about 2 months ago
liked
2
models
about 2 months ago
reacted to
DawnC's
post with 🤗
about 2 months ago
Post
1426
💡 Curious about dog breeds? 🐕 Meet PawMatchAI!
I've created this fun and interactive project to help you recognize dog breeds, find the perfect pup for your lifestyle, and even compare different breeds! Recently upgraded with smarter AI detection - it can now better distinguish between dogs and non-dogs (no more confusing cats for huskies! 😺➡️🐕).
🐾 What's cool about it?
Smart breed recognition powered by AI
Lifestyle-based breed recommendations
Detailed breed comparisons
And now with enhanced non-dog filtering!
🌟 Why try it?
Whether you're a dog lover, considering a new furry friend, or just curious, PawMatchAI makes discovering breeds fun and informative! As someone passionate about both AI and pets, I'm combining my two loves while working toward my goal of contributing to the AI industry.
🔎 Got feedback?
While it's not perfect, your input helps make it better! I'd love to hear your thoughts as I continue improving this project on my journey into AI development.
👉 Try it now: DawnC/PawMatchAI
🎯 Your support matters!
Every like 👍 or comment 📝 helps fuel my passion for AI development and keeps me motivated to create more helpful tools. Let's make the AI journey fun and impactful together!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision
I've created this fun and interactive project to help you recognize dog breeds, find the perfect pup for your lifestyle, and even compare different breeds! Recently upgraded with smarter AI detection - it can now better distinguish between dogs and non-dogs (no more confusing cats for huskies! 😺➡️🐕).
🐾 What's cool about it?
Smart breed recognition powered by AI
Lifestyle-based breed recommendations
Detailed breed comparisons
And now with enhanced non-dog filtering!
🌟 Why try it?
Whether you're a dog lover, considering a new furry friend, or just curious, PawMatchAI makes discovering breeds fun and informative! As someone passionate about both AI and pets, I'm combining my two loves while working toward my goal of contributing to the AI industry.
🔎 Got feedback?
While it's not perfect, your input helps make it better! I'd love to hear your thoughts as I continue improving this project on my journey into AI development.
👉 Try it now: DawnC/PawMatchAI
🎯 Your support matters!
Every like 👍 or comment 📝 helps fuel my passion for AI development and keeps me motivated to create more helpful tools. Let's make the AI journey fun and impactful together!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision
reacted to
MoritzLaurer's
post with 👍
about 2 months ago
Post
1292
I've been building a small library for working with prompt templates on the HF hub:
The community currently shares prompt templates in a wide variety of formats: in datasets, in model cards, as strings in .py files, as .txt/.yaml/.json/.jinja2 files etc. This makes sharing and working with prompt templates unnecessarily complicated.
Prompt templates are currently the main hyperparameter that people tune when building complex LLM systems or agents. If we don't have a common standard for sharing them, we cannot systematically test and improve our systems. After comparing different community approaches, I think that working with modular .yaml or .json files is the best approach.
The
- proposes a standard for sharing prompts (entirely locally or on the HF hub)
- provides some utilities that are interoperable with the broader ecosystem
Try it:
The library is in early stages, feedback is welcome!
More details in the docs: https://github.com/MoritzLaurer/prompt_templates/
pip install prompt-templates. Motivation: The community currently shares prompt templates in a wide variety of formats: in datasets, in model cards, as strings in .py files, as .txt/.yaml/.json/.jinja2 files etc. This makes sharing and working with prompt templates unnecessarily complicated.
Prompt templates are currently the main hyperparameter that people tune when building complex LLM systems or agents. If we don't have a common standard for sharing them, we cannot systematically test and improve our systems. After comparing different community approaches, I think that working with modular .yaml or .json files is the best approach.
The
prompt-templates library : - proposes a standard for sharing prompts (entirely locally or on the HF hub)
- provides some utilities that are interoperable with the broader ecosystem
Try it:
# !pip install prompt-templates
from prompt_templates import PromptTemplateLoader
prompt_template = PromptTemplateLoader.from_hub(repo_id="MoritzLaurer/closed_system_prompts", filename="claude-3-5-artifacts-leak-210624.yaml")The library is in early stages, feedback is welcome!
More details in the docs: https://github.com/MoritzLaurer/prompt_templates/
- 1 reply
reacted to
julien-c's
post with 😎
about 2 months ago
Post
9322
After some heated discussion 🔥, we clarify our intent re. storage limits on the Hub
TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)
docs: https://huggingface.co/docs/hub/storage-limits
We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community 🔥
cc: @reach-vb @pierric @victor and the HF team
TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)
docs: https://huggingface.co/docs/hub/storage-limits
We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community 🔥
cc: @reach-vb @pierric @victor and the HF team
- 28 replies