What are the hardware requirements for Cancer Llama.5 Llm?

Cancer Llama.5 Llm requires approximately 4.1 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 Cancer Llama.5 Llm and how large is it?

Cancer Llama.5 Llm is developed by Shivanikumar. 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 Cancer Llama.5 Llm?

Cancer Llama.5 Llm is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Cancer Llama.5 Llm by Shivanikumar — VRAM 4.1GB, 4K context

Name: Cancer Llama.5 Llm
Author: Shivanikumar

Cancer Llama.5 Llm is an open-source language model by Shivanikumar. Features: LLM, VRAM: 4.1GB, Context: 4K, Quantized, LLM Explorer Score: 0.12.

Endpoints compatible Gguf Llama Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/Shivanikumar/Cancer_Llama.5-llm

Cancer Llama.5 Llm Parameters and Internals

LLM Name	Cancer Llama.5 Llm
Repository 🤗	https://huggingface.co/Shivanikumar/Cancer_Llama.5-llm
Required VRAM	4.1 GB
Updated	2026-08-05
Maintainer	Shivanikumar
Model Type	llama
Model Files	4.1 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	LlamaForCausalLM
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0
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 Cancer Llama.5 Llm 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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LLAMA2 GOOD GGUF	16K / 4.8 GB	15	0
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...LaMA3 Iterative DPO Final GGUF	8K / 16.1 GB	13	1
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UlizaLlama Q4 K M Gguf	4K / 4.2 GB	76	0
Tinyllama Coder Py V15	4K / 0.7 GB	98	0
Tinyllama Coder Py V16	4K / 0.7 GB	12	0
Airavata GGUF	4K / 4.2 GB	43	2

Note: green Score (e.g. "73.2") means that the model is better than Shivanikumar/Cancer_Llama.5-llm.