What are the hardware requirements for Llama Finetune 16bit Wiki 250 Ver2 GPTQ?

Llama Finetune 16bit Wiki 250 Ver2 GPTQ requires approximately 5.8 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama Finetune 16bit Wiki 250 Ver2 GPTQ and how large is it?

Llama Finetune 16bit Wiki 250 Ver2 GPTQ is developed by obamaTeo, a model with 2b 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 Llama Finetune 16bit Wiki 250 Ver2 GPTQ?

Llama Finetune 16bit Wiki 250 Ver2 GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama Finetune 16bit Wiki 250 Ver2 GPTQ by obamaTeo — VRAM 5.8GB, 8K context

Name: Llama Finetune 16bit Wiki 250 Ver2 GPTQ
Author: obamaTeo

Llama Finetune 16bit Wiki 250 Ver2 GPTQ is an open-source language model by obamaTeo. Features: 2b LLM, VRAM: 5.8GB, Context: 8K, Quantized, Fine-Tuned, LLM Explorer Score: 0.12.

Arxiv:1910.09700 16bit 4-bit Autotrain compatible Conversational Endpoints compatible Finetuned Gptq Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/obamaTeo/llama-finetune-16bit-wiki-250-ver2-GPTQ

Llama Finetune 16bit Wiki 250 Ver2 GPTQ Parameters and Internals

LLM Name	Llama Finetune 16bit Wiki 250 Ver2 GPTQ
Repository 🤗	https://huggingface.co/obamaTeo/llama-finetune-16bit-wiki-250-ver2-GPTQ
Model Size	2b
Required VRAM	5.8 GB
Updated	2025-08-18
Maintainer	obamaTeo
Model Type	llama
Model Files	4.7 GB: 1-of-2 1.1 GB: 2-of-2
GPTQ Quantization	Yes
Quantization Type	gptq\|16bit
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.41.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|reserved_special_token_250\|>
Vocabulary Size	128256
Torch Data Type	float16

Rank the Llama Finetune 16bit Wiki 250 Ver2 GPTQ 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 Llama Finetune 16bit Wiki 250 Ver2 GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
MiniCPM5 2B GPTQ	128K / 2.1 GB	82	13
MiniCPM5 2B Chat Mlx 4bit	128K / 1.4 GB	232	2
MiniCPM5 2B 8bit	128K / 2.7 GB	734	6
MiniCPM5 2B OptiQ 4bit	128K / 1.9 GB	317	3
MiniCPM5 2B Mlx 4Bit	128K / 1.4 GB	286	1
MiniCPM5 2B MLX 8bit	128K / 2.7 GB	193	3
MiniCPM5 2B MLX 6bit	128K / 2 GB	192	1
MiniCPM5 2B MLX 4bit	128K / 1.4 GB	116	2
...ll Slm 2B Safetensors Mlx 4Bit	8K / 1 GB	267	4
MiniCPM5 2B Base	512K / 5 GB	54	17

Note: green Score (e.g. "73.2") means that the model is better than obamaTeo/llama-finetune-16bit-wiki-250-ver2-GPTQ.