What are the hardware requirements for NewMes V15?

NewMes V15 requires approximately 16.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed NewMes V15 and how large is it?

NewMes V15 is developed by bongbongs, a model with 8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does NewMes V15 perform on standard benchmarks?

NewMes V15 has the following published scores: LMSYS ELO 1177. Compare against reference models on this page or on the LLM Explorer leaderboards.

NewMes V15 by bongbongs — VRAM 16.1GB

Name: NewMes V15
Author: bongbongs

NewMes V15 is an open-source language model by bongbongs. Features: 8b LLM, VRAM: 16.1GB, License: llama3, LLM Explorer Score: 0.25, ELO: 1177.

Autotrain compatible Conversational Endpoints compatible Llama Lora Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/bongbongs/NewMes-v15

NewMes V15 Benchmarks

LMSys ELO 1177 vs 1272 (so35) -7.5%

^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)

NewMes V15 Parameters and Internals

Model Type

LLM

Supported Languages

English (NLP)

Training Details

Methodology:

Fine-tuned on medical training datasets

LLM Name	NewMes V15
Repository 🤗	https://huggingface.co/bongbongs/NewMes-v15
Model Size	8b
Required VRAM	16.1 GB
Updated	2025-01-15
Maintainer	bongbongs
Model Files	0.1 GB 4.0 GB: 1-of-5 3.9 GB: 2-of-5 3.9 GB: 3-of-5 3.2 GB: 4-of-5 1.1 GB: 5-of-5
Model Architecture	AutoModelForCausalLM
License	llama3
Is Biased	none
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	o_proj\|q_proj\|gate_proj\|k_proj\|v_proj\|down_proj\|up_proj
LoRA Alpha	32
LoRA Dropout	0.1
R Param	16

Rank the NewMes V15 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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