What are the hardware requirements for Codellama2 Finetuned Spiderdata?

Codellama2 Finetuned Spiderdata requires approximately 13.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Codellama2 Finetuned Spiderdata and how large is it?

Codellama2 Finetuned Spiderdata is developed by MerziaAdamjee, 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 Codellama2 Finetuned Spiderdata?

Codellama2 Finetuned Spiderdata is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Codellama2 Finetuned Spiderdata by MerziaAdamjee — VRAM 13.5GB

Name: Codellama2 Finetuned Spiderdata
Author: MerziaAdamjee

Codellama2 Finetuned Spiderdata is an open-source language model by MerziaAdamjee. Features: 7b LLM, VRAM: 13.5GB, License: llama2, Fine-Tuned, Instruction-Based, Code Generating, LLM Explorer Score: 0.09.

Base model:codellama/codellama... Base model:finetune:codellama/... Codegen Endpoints compatible Finetuned Generated from trainer Instruct Llama Lora Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/MerziaAdamjee/codellama2-finetuned-spiderdata

Codellama2 Finetuned Spiderdata Parameters and Internals

Additional Notes

This model is fine-tuned specifically with the spiderdata. Many sections on model description, intended uses, and other specific details were marked as 'More information needed'.

LLM Name	Codellama2 Finetuned Spiderdata
Repository 🤗	https://huggingface.co/MerziaAdamjee/codellama2-finetuned-spiderdata
Base Model(s)	CodeLlama 7B Instruct Hf codellama/CodeLlama-7b-Instruct-hf
Model Size	7b
Required VRAM	13.5 GB
Updated	2026-07-28
Maintainer	MerziaAdamjee
Instruction-Based	Yes
Model Files	0.0 GB 10.0 GB: 1-of-2 3.5 GB: 2-of-2 0.0 GB
Generates Code	Yes
Model Architecture	AutoModelForCausalLM
License	llama2
Is Biased	none
Tokenizer Class	CodeLlamaTokenizer
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|v_proj
LoRA Alpha	16
LoRA Dropout	0.05
R Param	8

Rank the Codellama2 Finetuned Spiderdata 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

Best Alternatives to Codellama2 Finetuned Spiderdata

Best Alternatives	Context / RAM	Downloads	Likes
Zyr3 V1	0K / 0.1 GB	206	1
Code Llama Python	0K / 0.3 GB	4	1
...ama2 Finetuned Spiderdata Copy	0K / 0 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than MerziaAdamjee/codellama2-finetuned-spiderdata.