What are the hardware requirements for QCammel 13 AWQ?

QCammel 13 AWQ requires approximately 7.2 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed QCammel 13 AWQ and how large is it?

QCammel 13 AWQ is developed by TheBloke, a model with 13b 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 QCammel 13 AWQ?

QCammel 13 AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

QCammel 13 AWQ by TheBloke — VRAM 7.2GB, 4K context

Name: QCammel 13 AWQ
Author: TheBloke

QCammel 13 AWQ is an open-source language model by TheBloke. Features: 13b LLM, VRAM: 7.2GB, Context: 4K, License: other, Quantized, LLM Explorer Score: 0.09.

Arxiv:2302.13971 Arxiv:2305.12031 Arxiv:2305.14314 4-bit Awq Base model:augtoma/qcammel-13 Base model:quantized:augtoma/q... En Llama Llama2 Pytorch Qcammel-13 Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/qCammel-13-AWQ

QCammel 13 AWQ Parameters and Internals

Model Type

llama

Training Details

Data Volume:

Distilled dataset of 15,000 instructions

Methodology:

QLoRA

Model Architecture:

Llama 2 architecture, an auto-regressive language model using a decoder only transformer architecture.

Input Output

Input Format:

Text input

Accepted Modalities:

text

Output Format:

Text output

LLM Name	QCammel 13 AWQ
Repository 🤗	https://huggingface.co/TheBloke/qCammel-13-AWQ
Model Name	qCammel 13
Model Creator	augtoma
Base Model(s)	QCammel 13 augtoma/qCammel-13
Model Size	13b
Required VRAM	7.2 GB
Updated	2026-07-24
Maintainer	TheBloke
Model Type	llama
Model Files	7.2 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	other
Context Length	4096
Model Max Length	4096
Transformers Version	4.32.0.dev0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the QCammel 13 AWQ 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 QCammel 13 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Yarn Llama 2 13B 128K AWQ	128K / 7.2 GB	4	2
LongAlign 13B 64K AWQ	64K / 7.2 GB	4	2
...oboros L2 13B 2 1 YaRN 64K AWQ	64K / 7.2 GB	5	2
OrcaMaid V3 13B 32K AWQ	32K / 7.2 GB	5	4
OrcaMaid V2 FIX 13B 32K AWQ	32K / 7.2 GB	7	1
NexusRaven V2 13B AWQ	16K / 7.2 GB	11	3
NexusRaven V2 13B AWQ	16K / 7.2 GB	1	3
...th CodeLlama 13B Python Hf AWQ	16K / 7.5 GB	6	0
WhiteRabbitNeo 13B AWQ	16K / 7.2 GB	332	4
NexusRaven V2 13B AWQ	16K / 7.2 GB	10	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/qCammel-13-AWQ.