alexgusevski/Huihui-HY-MT1.5-7B-abliterated-q2-mlx

This model alexgusevski/Huihui-HY-MT1.5-7B-abliterated-q2-mlx was converted to MLX format from huihui-ai/Huihui-HY-MT1.5-7B-abliterated using mlx-lm version 0.30.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("alexgusevski/Huihui-HY-MT1.5-7B-abliterated-q2-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, return_dict=False,
    )

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

README.md说明 / 使用方法

base_model: huihui-ai/Huihui-HY-MT1.5-7B-abliterated library_name: mlx tags:

translation
abliterated
uncensored
mlx language:
zh
en
fr
pt
es
ja
tr
ru
ar
ko
th
it
de
vi
ms
id
tl
hi
pl
cs
nl
km
my
fa
gu
ur
te
mr
he
bn
ta
uk
bo
kk
mn
ug pipeline_tag: text-generation

alexgusevski/Huihui-HY-MT1.5-7B-abliterated-q2-mlx

This model alexgusevski/Huihui-HY-MT1.5-7B-abliterated-q2-mlx was converted to MLX format from huihui-ai/Huihui-HY-MT1.5-7B-abliterated using mlx-lm version 0.30.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("alexgusevski/Huihui-HY-MT1.5-7B-abliterated-q2-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, return_dict=False,
    )

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