What are the hardware requirements for Llama 7B Onnx Merged Fp16?

Llama 7B Onnx Merged Fp16 requires a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 7B Onnx Merged Fp16 and how large is it?

Llama 7B Onnx Merged Fp16 is developed by nenkoru, a model with 7b 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 Llama 7B Onnx Merged Fp16?

Llama 7B Onnx Merged Fp16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 7B Onnx Merged Fp16 by nenkoru — 2K context

Name: Llama 7B Onnx Merged Fp16
Author: nenkoru

Llama 7B Onnx Merged Fp16 is an open-source language model by nenkoru. Features: 7b LLM, Context: 2K, License: other, Quantized, Merged, LLM Explorer Score: 0.06.

Merged Model Endpoints compatible Fp16 Llama Onnx Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/nenkoru/llama-7b-onnx-merged-fp16

Llama 7B Onnx Merged Fp16 Parameters and Internals

Model Type

auto-regressive, transformer

Use Cases

Areas:

research

Applications:

question answering, natural language understanding, reading comprehension, evaluating and mitigating biases and risks

Primary Use Cases:

research on large language models

Limitations:

Not for downstream applications without further risk evaluation, Potential for generating toxic or offensive content

Supported Languages

bg (basic), ca (basic), cs (basic), da (basic), de (basic), en (advanced), es (basic), fr (basic), hr (basic), hu (basic), it (basic), nl (basic), pl (basic), pt (basic), ro (basic), ru (basic), sl (basic), sr (basic), sv (basic), uk (basic)

Training Details

Data Sources:

CCNet, C4, GitHub, Wikipedia, Books, ArXiv, Stack Exchange

Model Architecture:

transformer

Responsible Ai Considerations

Fairness:

Performance varies with language use; mostly English data.

Transparency:

Evaluated using RAI datasets for various biases.

Mitigation Strategies:

Web data filtered for Wikipedia proximity using language models.

LLM Name	Llama 7B Onnx Merged Fp16
Repository 🤗	https://huggingface.co/nenkoru/llama-7b-onnx-merged-fp16
Base Model(s)	Llama 7B Onnx Merged Fp32 nenkoru/llama-7b-onnx-merged-fp32
Merged Model	Yes
Model Size	7b
Updated	2026-07-30
Maintainer	nenkoru
Model Type	llama
Quantization Type	fp16
Model Architecture	LLaMAForCausalLM
License	other
Context Length	2048
Model Max Length	2048
Transformers Version	4.28.0.dev0
Vocabulary Size	32000
Torch Data Type	float16

Rank the Llama 7B Onnx Merged Fp16 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 Llama 7B Onnx Merged Fp16

Best Alternatives	Context / RAM	Downloads	Likes
Alpaca 7B Native 4bit	0K / 4.5 GB	14	4
Alpaca Native 4bit	0K / 4.5 GB	6	58
Llama 7B 4bit Gr128	0K / 4 GB	11	4
Llama 7B 4bit Act	0K / 3.8 GB	11	2
Swallow 7B GPTQ	4K / 4.1 GB	5	1
Honest Llama2 Chat 7B	2K / 13.5 GB	212	9
Llama 7B Onnx Merged Fp32	2K / GB	12	1
Chatdoctor	0K / 27 GB	63	12
Explore LM 7B Math	0K / 27 GB	13	1
Explore LM Ext 7B Rewriting	0K / 27 GB	12	1

Note: green Score (e.g. "73.2") means that the model is better than nenkoru/llama-7b-onnx-merged-fp16.