What are the hardware requirements for QCammel 13 GGML?

QCammel 13 GGML requires approximately 5.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed QCammel 13 GGML and how large is it?

QCammel 13 GGML is developed by TheBloke. 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 GGML?

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

QCammel 13 GGML by TheBloke — VRAM 5.5GB

Name: QCammel 13 GGML
Author: TheBloke

QCammel 13 GGML is an open-source language model by TheBloke. Features: LLM, VRAM: 5.5GB, License: llama2, Quantized, LLM Explorer Score: 0.08.

Arxiv:2302.13971 Arxiv:2305.12031 Arxiv:2305.14314 Base model:augtoma/qcammel-13 Base model:finetune:augtoma/qc... En Ggml Llama Llama2 Pytorch Qcammel-13 Quantized Region:us

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

QCammel 13 GGML Parameters and Internals

Model Type

text generation

Use Cases

Applications:

academic medical knowledge, instruction-following capabilities

Additional Notes

qCammel-13 is a fine-tuned version optimized for academic medical knowledge and instruction-following capabilities based on the Llama 2 model.

Training Details

Data Volume:

15000 instructions

Methodology:

QLoRA fine-tuning

Model Architecture:

Llama 2 architecture, auto-regressive decoder transformer

Input Output

Input Format:

text only

Accepted Modalities:

text

Output Format:

text generation

LLM Name	QCammel 13 GGML
Repository 🤗	https://huggingface.co/TheBloke/qCammel-13-GGML
Model Name	qCammel 13
Model Creator	augtoma
Base Model(s)	QCammel 13 augtoma/qCammel-13
Required VRAM	5.5 GB
Updated	2026-08-03
Maintainer	TheBloke
Model Type	llama
Model Files	5.5 GB 6.9 GB 6.3 GB 5.7 GB 7.4 GB 8.2 GB 7.9 GB 7.4 GB 9.0 GB 9.8 GB 9.2 GB 9.0 GB 10.7 GB 13.8 GB
Supported Languages	en
GGML Quantization	Yes
Quantization Type	ggml
Model Architecture	AutoModel
License	llama2

Rank the QCammel 13 GGML 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 GGML

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Athena V1 GGML	0K / 5.5 GB	6	1
MythoMax Kimiko Mix GGML	0K / 5.7 GB	3	3
...ax22b Instruct Falseblock GGML	0K / 9.2 GB	7	6
Octocoder GGML	0K / 10.7 GB	7	15
PULI GPT 3SX GGML	0K / 3.9 GB	7	5
NewHope GGML	0K / 5.7 GB	6	38
Spring Dragon GGML	0K / 5.5 GB	3	3
QCammel 70 X GGML	0K / 28.6 GB	10	3
OpenChat V3.2 GGML	0K / 5.7 GB	5	14
Replit Openorca GGML	0K / 1.5 GB	6	6

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