Mangosteen: An Open Thai Corpus for Language Model Pretraining
Paper
β’
2507.14664
β’
Published
β’
6
Sailor2
community
AI & ML interests
Open language models for South-East Asia
Recent Activity
View all activity
wannaphongΒ
authored
a
paper
21 days ago
Post
3868
π Dhanishtha-2.0-preview-0825 Is Here
The Intermediate Thinking Model just leveled up again.
With sharper reasoning, better tool use, and expanded capabilities, Dhanishtha-2.0-preview-0825 is now live and ready to impress.
π§ What Makes Dhanishtha Special?
Unlike typical CoT models that only thinks one time, Dhanishtha thinks iteratively:
> Think β Answer β Rethink β Improve β Rethink again if needed.
π Try it now: HelpingAI/Dhanishtha-2.0-preview-0825
π Dhanishtha NSFW Preview
For those exploring more expressive and immersive roleplay scenarios, weβre also releasing:
HelpingAI/Dhanishtha-nsfw
A specialized version tuned for adult-themed interactions and character-driven roleplay.
π Explore it here: HelpingAI/Dhanishtha-nsfw
π¬ You can also try all of these live at chat.helpingai.co
The Intermediate Thinking Model just leveled up again.
With sharper reasoning, better tool use, and expanded capabilities, Dhanishtha-2.0-preview-0825 is now live and ready to impress.
π§ What Makes Dhanishtha Special?
Unlike typical CoT models that only thinks one time, Dhanishtha thinks iteratively:
> Think β Answer β Rethink β Improve β Rethink again if needed.
π Try it now: HelpingAI/Dhanishtha-2.0-preview-0825
π Dhanishtha NSFW Preview
For those exploring more expressive and immersive roleplay scenarios, weβre also releasing:
HelpingAI/Dhanishtha-nsfw
A specialized version tuned for adult-themed interactions and character-driven roleplay.
π Explore it here: HelpingAI/Dhanishtha-nsfw
π¬ You can also try all of these live at chat.helpingai.co
- 4 replies
gabrielchuaΒ
authored
3
papers
about 1 month ago
Running in CIRCLE? A Simple Benchmark for LLM Code Interpreter Security
Paper
β’
2507.19399
β’
Published
β’
1
LionGuard 2: Building Lightweight, Data-Efficient & Localised Multilingual Content Moderators
Paper
β’
2507.15339
β’
Published
Toxicity-Aware Few-Shot Prompting for Low-Resource Singlish Translation
Paper
β’
2507.11966
β’
Published
SivilTaramΒ
authored
a
paper
about 1 month ago
Post
3059
π Dhanishtha-2.0-preview-0725 is Now Live
The Intermediate Thinking Model just got even better.
With the new update, Dhanishtha is now sharper, smarter, and trained further on tool use
π§ What Makes Dhanishtha Different?
Unlike standard COT models that give one-shot responses, Dhanishtha thinks in layers:
> Think β Answer β Rethink β Improve β Rethink again if needed.
HelpingAI/Dhanishtha-2.0-preview-0725
The Intermediate Thinking Model just got even better.
With the new update, Dhanishtha is now sharper, smarter, and trained further on tool use
π§ What Makes Dhanishtha Different?
Unlike standard COT models that give one-shot responses, Dhanishtha thinks in layers:
> Think β Answer β Rethink β Improve β Rethink again if needed.
HelpingAI/Dhanishtha-2.0-preview-0725
gabrielchuaΒ
authored
a
paper
about 1 month ago
SivilTaramΒ
authored
a
paper
about 2 months ago
gabrielchuaΒ
authored
a
paper
about 2 months ago
SivilTaramΒ
authored
a
paper
about 2 months ago
Post
3026
π Dhanishtha 2.0 Preview is Now Open Source!
The world's first Intermediate Thinking Model is now available to everyone!
Dhanishtha 2.0 Preview brings revolutionary intermediate thinking capabilities to the open-source community. Unlike traditional reasoning models that think once, Dhanishtha can think, answer, rethink, answer again, and continue rethinking as needed using multiple
π Key Features
- Intermediate thinking: Think β Answer β Rethink β Answer β Rethink if needed...
- Token efficient: Uses up to 79% fewer tokens than DeepSeek R1 on similar queries
- Transparent thinking: See the model's reasoning process in real-time
- Open source: Freely available for research and development
HelpingAI/Dhanishtha-2.0-preview
https://helpingai.co/chat
The world's first Intermediate Thinking Model is now available to everyone!
Dhanishtha 2.0 Preview brings revolutionary intermediate thinking capabilities to the open-source community. Unlike traditional reasoning models that think once, Dhanishtha can think, answer, rethink, answer again, and continue rethinking as needed using multiple
π Key Features
- Intermediate thinking: Think β Answer β Rethink β Answer β Rethink if needed...
- Token efficient: Uses up to 79% fewer tokens than DeepSeek R1 on similar queries
- Transparent thinking: See the model's reasoning process in real-time
- Open source: Freely available for research and development
HelpingAI/Dhanishtha-2.0-preview
https://helpingai.co/chat
- 1 reply
koalazf99Β
authored
a
paper
2 months ago
dreamerdeoΒ
updated
a
Space
2 months ago
Post
4491
Introducing Dhanishtha 2.0: World's first Intermediate Thinking Model
Dhanishtha 2.0 is the world's first LLM designed to think between the responses. Unlike other Reasoning LLMs, which think just once.
Dhanishtha can think, rethink, self-evaluate, and refine in between responses using multiple <think> blocks.
This technique makes it Hinghlt Token efficient it Uses up to 79% fewer tokens than DeepSeek R1
---
You can try our model from: https://helpingai.co/chat
Also, we're gonna Open-Source Dhanistha on July 1st.
---
For Devs:
π Get your API key at https://helpingai.co/dashboard
Dhanishtha 2.0 is the world's first LLM designed to think between the responses. Unlike other Reasoning LLMs, which think just once.
Dhanishtha can think, rethink, self-evaluate, and refine in between responses using multiple <think> blocks.
This technique makes it Hinghlt Token efficient it Uses up to 79% fewer tokens than DeepSeek R1
---
You can try our model from: https://helpingai.co/chat
Also, we're gonna Open-Source Dhanistha on July 1st.
---
For Devs:
π Get your API key at https://helpingai.co/dashboard
from HelpingAI import HAI # pip install HelpingAI==1.1.1
from rich import print
hai = HAI(api_key="hl-***********************")
response = hai.chat.completions.create(
model="Dhanishtha-2.0-preview",
messages=[{"role": "user", "content": "What is the value of β«0βπ₯3/π₯β1ππ₯ ?"}],
stream=True,
hide_think=False # Hide or show models thinking
)
for chunk in response:
print(chunk.choices[0].delta.content, end="", flush=True)
- 2 replies
gentaiscoolΒ
authored
a
paper
2 months ago
koalazf99Β
authored
a
paper
2 months ago
joanitolopoΒ
authored
a
paper
2 months ago
saksornrΒ
authored
a
paper
2 months ago
joanitolopoΒ
authored
a
paper
2 months ago