metadata
library_name: mlx
license: apache-2.0
pipeline_tag: text-generation
base_model: Jinx-org/Jinx-gpt-oss-20b-mxfp4
tags:
- vllm
- mlx
extra_gated_heading: >-
You need to read and agree to the Disclaimer and User Agreementa to access
this model.
extra_gated_description: >-
## Disclaimer and User Agreement
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Thank you for your interest in accessing this model (“the Model”).
Before you access, download, or use the Model or any derivative works, please
read and understand this Disclaimer and User Agreement (“Agreement”).
By checking “I have read and agree” and accessing the Model, you acknowledge
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If you do not agree with any part of this Agreement, do not request or use the
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The Model is trained using large-scale machine learning techniques and may
generate inaccurate, false, offensive, violent, sexual, discriminatory,
politically sensitive, or otherwise uncontrolled content.
The Model does not guarantee the accuracy, completeness, or legality of any
generated content. You must independently evaluate and verify the outputs, and
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mlx-community/Jinx-gpt-oss-20b-mxfp4-mlx
This model mlx-community/Jinx-gpt-oss-20b-mxfp4-mlx was converted to MLX format from Jinx-org/Jinx-gpt-oss-20b-mxfp4 using mlx-lm version 0.27.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Jinx-gpt-oss-20b-mxfp4-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)