What are the hardware requirements for QCammel 70 X GPTQ?

QCammel 70 X GPTQ requires approximately 35.3 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 70 X GPTQ and how large is it?

QCammel 70 X GPTQ is developed by TheBloke, a model with 69b 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 70 X GPTQ?

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

QCammel 70 X GPTQ by TheBloke — VRAM 35.3GB, 4K context

Name: QCammel 70 X GPTQ
Author: TheBloke

QCammel 70 X GPTQ is an open-source language model by TheBloke. Features: 69b LLM, VRAM: 35.3GB, Context: 4K, License: other, Quantized, LLM Explorer Score: 0.08.

Arxiv:2302.70971 Arxiv:2305.12031 Arxiv:2305.14314 4-bit Base model:augtoma/qcammel-70-... Base model:quantized:augtoma/q... En Gptq Llama Llama2 Pytorch Qcammel-70 Quantized Region:us Safetensors

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

QCammel 70 X GPTQ Parameters and Internals

Model Type

llama

Additional Notes

Optimized for academic medical knowledge and instruction-following capabilities.

Training Details

Methodology:

The fine-tuning process applied to qCammel-70 involves a distilled dataset of 15,000 instructions and is trained with QLoRA.

Model Architecture:

qCammel-70 is based on the Llama 2 architecture, an auto-regressive language model that uses a decoder only transformer architecture.

Input Output

Input Format:

Text input.

Output Format:

Text output.

LLM Name	QCammel 70 X GPTQ
Repository 🤗	https://huggingface.co/TheBloke/qCammel-70-x-GPTQ
Model Name	qCammel 70
Model Creator	augtoma
Base Model(s)	QCammel 70 X augtoma/qCammel-70-x
Model Size	69b
Required VRAM	35.3 GB
Updated	2026-07-30
Maintainer	TheBloke
Model Type	llama
Model Files	35.3 GB
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
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 70 X 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 QCammel 70 X GPTQ

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...ine Tu Ophtho 3 1e 05 Stanford	4K / 138.7 GB	5	0
StableBeluga2	4K / 1.7 GB	15937	20
V Alpha Tross	4K / 138.7 GB	74	20
Uni TianYan V1	4K / 138 GB	66	0
SaiLy Experiment V1	4K / 276 GB	15	2
Airoboros L2 C70b 3.1.2	4K / 138 GB	79	0
QCammel 70 X AWQ	4K / 36.6 GB	6	1
Model 007 Preview	4K / 138 GB	29	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/qCammel-70-x-GPTQ.