What are the hardware requirements for CodelLama7B Inst DPO 7K Mlx?

CodelLama7B Inst DPO 7K Mlx requires approximately 4.2 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed CodelLama7B Inst DPO 7K Mlx and how large is it?

CodelLama7B Inst DPO 7K Mlx is developed by mlx-community, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate CodelLama7B Inst DPO 7K Mlx?

CodelLama7B Inst DPO 7K Mlx is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

CodelLama7B Inst DPO 7K Mlx by mlx-community — VRAM 4.2GB, 16K context

Name: CodelLama7B Inst DPO 7K Mlx
Author: mlx-community

CodelLama7B Inst DPO 7K Mlx is an open-source language model by mlx-community. Features: 7b LLM, VRAM: 4.2GB, Context: 16K, License: llama2, Quantized, Instruction-Based, Code Generating, LLM Explorer Score: 0.11.

4bit Code Codegen Instruct Llama Llama2 Mlx Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mlx-community/CodelLama7B-inst-dpo-7k-mlx

CodelLama7B Inst DPO 7K Mlx Parameters and Internals

Model Type

text-generation

Training Details

Data Sources:

argilla 7k DPO dataset

LLM Name	CodelLama7B Inst DPO 7K Mlx
Repository 🤗	https://huggingface.co/mlx-community/CodelLama7B-inst-dpo-7k-mlx
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-08-08
Maintainer	mlx-community
Model Type	llama
Instruction-Based	Yes
Model Files	4.2 GB
Supported Languages	code
Quantization Type	4bit
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.37.2
Vocabulary Size	32016
Torch Data Type	bfloat16

Rank the CodelLama7B Inst DPO 7K Mlx capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Note: green Score (e.g. "73.2") means that the model is better than mlx-community/CodelLama7B-inst-dpo-7k-mlx.