What are the hardware requirements for Gemma 7B Custom Tokenizer Base?

Gemma 7B Custom Tokenizer Base requires approximately 34 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 7B Custom Tokenizer Base and how large is it?

Gemma 7B Custom Tokenizer Base is developed by PolyAgent, 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 Gemma 7B Custom Tokenizer Base?

Gemma 7B Custom Tokenizer Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 7B Custom Tokenizer Base by PolyAgent — VRAM 34GB, 8K context

Name: Gemma 7B Custom Tokenizer Base
Author: PolyAgent

Gemma 7B Custom Tokenizer Base is an open-source language model by PolyAgent. Features: 7b LLM, VRAM: 34GB, Context: 8K, License: gemma, LLM Explorer Score: 0.14.

Autotrain compatible Endpoints compatible Gemma Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/PolyAgent/gemma-7b-custom-tokenizer-base

Gemma 7B Custom Tokenizer Base Benchmarks

LLME Score: 0.14097

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Gemma 7B Custom Tokenizer Base (PolyAgent/gemma-7b-custom-tokenizer-base)

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Gemma 7B Custom Tokenizer Base Parameters and Internals

LLM Name	Gemma 7B Custom Tokenizer Base
Repository 🤗	https://huggingface.co/PolyAgent/gemma-7b-custom-tokenizer-base
Model Size	7b
Required VRAM	34 GB
Updated	2024-10-24
Maintainer	PolyAgent
Model Type	gemma
Model Files	4.8 GB: 1-of-8 4.7 GB: 2-of-8 4.9 GB: 3-of-8 4.7 GB: 4-of-8 4.7 GB: 5-of-8 4.9 GB: 6-of-8 4.7 GB: 7-of-8 0.6 GB: 8-of-8
Model Architecture	GemmaForCausalLM
License	gemma
Context Length	8192
Model Max Length	8192
Transformers Version	4.41.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float32

Best Alternatives to Gemma 7B Custom Tokenizer Base

Best Alternatives	Context / RAM	Downloads	Likes
Kaggle Math Model Gemma V1	12K / 17.1 GB	5	0
Gemma 1.1 7B It	8K / 17.1 GB	12200	275
Gemma 1.1 7B It	8K / 17.1 GB	12	4
Gemma 7B It	8K / 17.1 GB	1570	10
SeaLLM 7B V2.5	8K / 17.1 GB	12476	51
Zephyr 7B Gemma DPO Avg	8K / 17.1 GB	15	0
Zephyr 7B Gemma Rpo Avg	8K / 17.1 GB	7	0
... 7B Finetuned Sft Navarasa 2.0	8K / 34 GB	1620	23
... Codegemma 2 7B It Alpaca V1.3	8K / 17.1 GB	2	1
Codegemma 7B It	8K / 17.1 GB	8430	252

Note: green Score (e.g. "73.2") means that the model is better than PolyAgent/gemma-7b-custom-tokenizer-base.

Rank the Gemma 7B Custom Tokenizer Base Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a

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Gemma 7B Custom Tokenizer Base by PolyAgent

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Gemma 7B Custom Tokenizer Base Benchmarks

Gemma 7B Custom Tokenizer Base Parameters and Internals

Best Alternatives to Gemma 7B Custom Tokenizer Base

Rank the Gemma 7B Custom Tokenizer Base Capabilities

What open-source LLMs or SLMs are you in search of? 53972 in total.