metadata

language:
  - en
  - hi
  - zh
  - es
  - fr
  - de
  - ja
  - ko
  - ar
  - pt
  - ru
  - it
  - nl
  - tr
  - pl
  - sv
  - da
  - 'no'
  - fi
  - he
  - th
  - vi
  - id
  - ms
  - tl
  - sw
  - yo
  - zu
  - am
  - bn
  - gu
  - kn
  - ml
  - mr
  - ne
  - or
  - pa
  - ta
  - te
  - ur
  - multilingual
license: apache-2.0
base_model: HelpingAI/Dhanishtha-2.0-preview-0825
tags:
  - reasoning
  - intermediate-thinking
  - transformers
  - conversational
  - bilingual
  - mlx
datasets:
  - Abhaykoul/Dhanishtha-R1
  - open-thoughts/OpenThoughts-114k
  - Abhaykoul/Dhanishtha-2.0-SUPERTHINKER
  - Abhaykoul/Dhanishtha-2.0
library_name: mlx
pipeline_tag: text-generation
widget:
  - text: >-
      Solve this riddle step by step: I am taken from a mine, and shut up in a
      wooden case, from which I am never released, and yet I am used by almost
      everybody. What am I?
    example_title: Complex Riddle Solving
  - text: >-
      Explain the philosophical implications of artificial consciousness and
      think through different perspectives.
    example_title: Philosophical Reasoning
  - text: >-
      Help me understand quantum mechanics, but take your time to think through
      the explanation.
    example_title: Educational Explanation

Dhanishtha-2.0-preview-0825-q8-hi-mlx

This model Dhanishtha-2.0-preview-0825-q8-hi-mlx was converted to MLX format from HelpingAI/Dhanishtha-2.0-preview-0825 using mlx-lm version 0.26.1.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("Dhanishtha-2.0-preview-0825-q8-hi-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)