base_model, datasets, language, license, pipeline_tag, tags, extra_gated_prompt, extra_gated_fields, model-index

base_model	datasets	language	license	pipeline_tag	tags	extra_gated_prompt	extra_gated_fields	model-index
pints-ai/1.5-Pints-16K-v0.1	pints-ai/Expository-Prose-V1 HuggingFaceH4/ultrachat_200k Open-Orca/SlimOrca-Dedup meta-math/MetaMathQA HuggingFaceH4/deita-10k-v0-sft WizardLM/WizardLM_evol_instruct_V2_196k togethercomputer/llama-instruct LDJnr/Capybara HuggingFaceH4/ultrafeedback_binarized	en	mit	text-generation	mlx	Though best efforts has been made to ensure, as much as possible, that all texts in the training corpora are royalty free, this does not constitute a legal guarantee that such is the case. **By using any of the models, corpora or part thereof, the user agrees to bear full responsibility to do the necessary due diligence to ensure that he / she is in compliance with their local copyright laws. Additionally, the user agrees to bear any damages arising as a direct cause (or otherwise) of using any artifacts released by the pints research team, as well as full responsibility for the consequences of his / her usage (or implementation) of any such released artifacts. The user also indemnifies Pints Research Team (and any of its members or agents) of any damage, related or unrelated, to the release or subsequent usage of any findings, artifacts or code by the team. For the avoidance of doubt, any artifacts released by the Pints Research team are done so in accordance with the 'fair use' clause of Copyright Law, in hopes that this will aid the research community in bringing LLMs to the next frontier.	Company Country Specific date I want to use this model for I agree to use this model for in accordance to the afore-mentioned Terms of Use text country date_picker type options select Research Education label value Other other checkbox	name results 1.5-Pints task dataset metrics source type text-generation name type MTBench ai2_arc type value name LLM-as-a-Judge 3.4 MTBench url name https://huggingface.co/spaces/lmsys/mt-bench MTBench

mlx-community/1.5-Pints-16K-v0.1

The Model mlx-community/1.5-Pints-16K-v0.1 was converted to MLX format from pints-ai/1.5-Pints-16K-v0.1 using mlx-lm version 0.19.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/1.5-Pints-16K-v0.1")

prompt="hello"

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

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