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LFM2.5 350M Tool Calling Merged V2 by mosama

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LFM2.5 350M Tool Calling Merged V2 is an open-source language model by mosama. Features: 350m LLM, VRAM: 0.7GB, Context: 125K, License: apache-2.0, Merged, LLM Explorer Score: 0.31.

  Merged Model Base model:finetune:mosama/lfm... Base model:mosama/lfm2.5-350m-...   Conversational   En   Endpoints compatible   Lfm2   Region:us   Safetensors   Unsloth
Model Card on HF 🤗: https://huggingface.co/mosama/LFM2.5-350M-Tool-Calling-Merged-v2 

LFM2.5 350M Tool Calling Merged V2 Benchmarks

LLME Score: 0.30987
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LFM2.5 350M Tool Calling Merged V2 (mosama/LFM2.5-350M-Tool-Calling-Merged-v2)
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LFM2.5 350M Tool Calling Merged V2 Parameters and Internals

LLM NameLFM2.5 350M Tool Calling Merged V2
Repository 🤗https://huggingface.co/mosama/LFM2.5-350M-Tool-Calling-Merged-v2 
Model Namemosama/LFM2.5-350M-Tool-Calling-Merged
Base Model(s)  mosama/LFM2.5-350M-Tool-Calling-Merged   mosama/LFM2.5-350M-Tool-Calling-Merged
Merged ModelYes
Model Size350m
Required VRAM0.7 GB
Updated2026-05-14
Maintainermosama
Model Typelfm2
Model Files  0.7 GB
Supported Languagesen
Model ArchitectureLfm2ForCausalLM
Licenseapache-2.0
Context Length128000
Model Max Length128000
Tokenizer ClassTokenizersBackend
Padding Token<|pad|>
Vocabulary Size65536
Torch Data Typebfloat16

Best Alternatives to LFM2.5 350M Tool Calling Merged V2

Best Alternatives
Context / RAM
Downloads
Likes
LFM2.5 350M125K / 0.7 GB108802299
LFM2.5 350M Base125K / 0.7 GB43809
LFM2.5 350M ONNX125K /  GB13224
LFM2 350M125K / 0.7 GB26177249
... Function Calling XLAM Unsloth125K / 0.7 GB5370
Terminus LFM2.5 350M125K / 0.7 GB4773
LFM2 350M CPT125K / 0.7 GB6320
LFM2.5 350M Home Assistant DPO125K / 0.7 GB550
....5 350M Home Assistant Sft V13125K / 0.7 GB490
SS 350M SQL Strict125K / 0.7 GB1743
Note: green Score (e.g. "73.2") means that the model is better than mosama/LFM2.5-350M-Tool-Calling-Merged-v2.

Rank the LFM2.5 350M Tool Calling Merged V2 Capabilities

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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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