What are the hardware requirements for QCammel 70 X GGML?

QCammel 70 X GGML requires approximately 28.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed QCammel 70 X GGML and how large is it?

QCammel 70 X 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 70 X GGML?

QCammel 70 X GGML is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

QCammel 70 X GGML by TheBloke — VRAM 28.6GB

Name: QCammel 70 X GGML
Author: TheBloke

QCammel 70 X GGML is an open-source language model by TheBloke. Features: LLM, VRAM: 28.6GB, License: llama2, Quantized, LLM Explorer Score: 0.08.

Arxiv:2302.70971 Arxiv:2305.12031 Arxiv:2305.14314 Base model:augtoma/qcammel-70-... Base model:finetune:augtoma/qc... En Ggml Llama Llama2 Pytorch Qcammel-70 Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/qCammel-70-x-GGML

QCammel 70 X GGML Parameters and Internals

Model Type

text-generation

Use Cases

Primary Use Cases:

academic medical knowledge, instruction-following

Additional Notes

Optimized for academic medical knowledge and instruction-following capabilities.

Training Details

Data Sources:

distilled dataset of 15,000 instructions

Methodology:

fine-tuning with QLoRA

Model Architecture:

auto-regressive language model using a decoder-only transformer architecture

Input Output

Input Format:

text

Output Format:

text

LLM Name	QCammel 70 X GGML
Repository 🤗	https://huggingface.co/TheBloke/qCammel-70-x-GGML
Model Name	qCammel 70
Model Creator	augtoma
Base Model(s)	QCammel 70 X augtoma/qCammel-70-x
Required VRAM	28.6 GB
Updated	2026-08-05
Maintainer	TheBloke
Model Type	llama
Model Files	28.6 GB 36.1 GB 33.0 GB 29.7 GB 38.9 GB 43.2 GB 41.4 GB 38.9 GB 47.5 GB 48.8 GB 47.5 GB
Supported Languages	en
GGML Quantization	Yes
Quantization Type	ggml
Model Architecture	AutoModel
License	llama2

Rank the QCammel 70 X 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

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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-70-x-GGML.