📢 For those who wish to apply DeepSeek-R1 for handling tabular / streaming data using schema of prompts (CoT), the OpenRouter AI hosts API for accessing: https://openrouter.ai/deepseek/deepseek-r1
📺 below is a screenshot of how to quick start the demo, in which you can test your schema for LLM responses. It would ask to type all the parameters first for completing the requests (which is text within this example).
📃 To apply it for JSONL/CSV data, you can use --src shell parameter for passing the related file
⏳ As for time, OpenRouter finds me relatively slow with 30~40 seconds per request
We are reproducing the full DeepSeek R1 data and training pipeline so everybody can use their recipe. Instead of doing it in secret we can do it together in the open!
🧪 Step 1: replicate the R1-Distill models by distilling a high-quality reasoning corpus from DeepSeek-R1.
🧠 Step 2: replicate the pure RL pipeline that DeepSeek used to create R1-Zero. This will involve curating new, large-scale datasets for math, reasoning, and code.
🔥 Step 3: show we can go from base model -> SFT -> RL via multi-stage training.
So 🐋DeepSeek🐋 hits the mainstream media. But it has been a star in our little cult for at least 6 months. Its meteoric success is not overnight, but two years in the making.
* End of 2023, they launched the first model (pretrained by themselves) following Llama 2 architecture * June 2024, v2 (MoE architecture) surpassed Gemini 1.5, but behind Mistral * September, v2.5 surpassed GPT 4o mini * December, v3 surpassed GPT 4o * Now R1 surpassed o1
Most importantly, if you think DeepSeek success is singular and unrivaled, that's WRONG. The following models are also near or equal the o1 bar.
Epic wuxia storytelling with real-time combat art Traditional martial arts world visualization Dynamic qi techniques in motion Beautiful Eastern art style generation
Hello to everyone who loves frog memes! Now you can generate fun images of Pepe in various scenarios. By using the DiffusionPipeline from Hugging Face and LoRA (a method of adding additional training data to a large model for a specific style), you can easily create Pepe characters.
The model card includes LoRA weights related to the Pepe character, allowing you to easily create meme-style images. On the Space page, you can generate Pepe images right away via the web UI without writing extra code!
⭐ Main Features Meme-Style Pepe Images
Enter prompts like “Pepe dancing excitedly” or “Pepe busking in the streets of New York,” and it automatically generates an image. From comical, cartoon-like memes to a somewhat serious(?) Pepe, you can achieve a wide variety of styles. LoRA Scale Adjustment
Change the LoRA scale parameter to fine-tune how strongly the Pepe style is applied. A value closer to 0 yields a more generic image, while a value closer to 1 results in a strongly cartoon-like Pepe appearance. Advanced Settings
Modify the Height and Width to generate vertical or horizontal images of different aspect ratios. Adjust Guidance scale and Inference steps to get the exact level of detail and artistic style you want. Seed Configuration
Choose a fixed seed or a random seed so that images are either reproducible or new every time. 🚀 Usage Ideas SNS Meme Creation
Quickly make fun Pepe images for Twitter or Instagram Stories. Perfect for events, birthdays, or any special occasion memes! Fan Art & Merch Design
Use generated images as references for Pepe fan art, or draft designs for merchandise (stickers, T-shirts, etc.). Blog & Community Posts
Spice up your blog articles or community posts with meme images. Set up humorous scenarios featuring Pepe as an entertaining “reaction image.”
✨ MIT License : enabling distillation for custom models ✨ 32B & 70B models match OpenAI o1-mini in multiple capabilities ✨ API live now! Access Chain of Thought reasoning with model='deepseek-reasoner'