What are the hardware requirements for Codellama 7B Instruct Slerp?

Codellama 7B Instruct Slerp requires approximately 13.4 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 Codellama 7B Instruct Slerp and how large is it?

Codellama 7B Instruct Slerp is developed by tyson0420, 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 Codellama 7B Instruct Slerp?

Codellama 7B Instruct Slerp is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Codellama 7B Instruct Slerp by tyson0420 — VRAM 13.4GB, 16K context

Name: Codellama 7B Instruct Slerp
Author: tyson0420

Codellama 7B Instruct Slerp is an open-source language model by tyson0420. Features: 7b LLM, VRAM: 13.4GB, Context: 16K, License: apache-2.0, Instruction-Based, Code Generating, Merged, LLM Explorer Score: 0.11.

Merged Model Codegen Endpoints compatible Instruct Llama Region:us Safetensors Sharded Tensorflow Tyson0420/alpaca codellama Tyson0420/stack-codellama-fil-...

Model Card on HF 🤗: https://huggingface.co/tyson0420/codellama-7B-instruct-slerp

Codellama 7B Instruct Slerp Parameters and Internals

Model Type

code generation

Additional Notes

Model is a blend of two models using mergekit, optimized for code-related tasks.

LLM Name	Codellama 7B Instruct Slerp
Repository 🤗	https://huggingface.co/tyson0420/codellama-7B-instruct-slerp
Merged Model	Yes
Model Size	7b
Required VRAM	13.4 GB
Updated	2026-07-17
Maintainer	tyson0420
Model Type	llama
Instruction-Based	Yes
Model Files	1.9 GB: 1-of-7 1.9 GB: 2-of-7 2.0 GB: 3-of-7 1.9 GB: 4-of-7 1.9 GB: 5-of-7 2.0 GB: 6-of-7 1.8 GB: 7-of-7
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	16384
Model Max Length	16384
Transformers Version	4.35.2
Tokenizer Class	CodeLlamaTokenizer
Vocabulary Size	32016
Torch Data Type	bfloat16

Rank the Codellama 7B Instruct Slerp 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

Quantized Models of the Codellama 7B Instruct Slerp

Model	Likes	Downloads	VRAM
CodeLlama 7B Instruct Fp16	7	24	13 GB

Best Alternatives to Codellama 7B Instruct Slerp

Best Alternatives	Context / RAM	Downloads	Likes
Deepseek Coder 6.7B Instruct	16K / 13.5 GB	535311	507
CodeLlama 7B Instruct Hf	16K / 13.5 GB	58587	258
GetCode Slerp	16K / 13.6 GB	87	1
Stack Codellama 7B Inst	16K / 13.5 GB	66	0
CodeV CL 7B	16K / 13.5 GB	430	1
CodeLlama 7B Instruct Hf	16K / 13.5 GB	2313	63
Glaive Coder 7B	16K / 27 GB	85	55
...deLlama 7B Instruct Hf 8bits Q	16K / 4.2 GB	18	1
Llama 2 7B Chat Finetune5	16K / 13.8 GB	3	1
...ama 7B Instruct Hf Dequantized	16K / 13.5 GB	197	0

Note: green Score (e.g. "73.2") means that the model is better than tyson0420/codellama-7B-instruct-slerp.