What are the hardware requirements for Smol Llama 220M Bees Internal?

Smol Llama 220M Bees Internal requires approximately 0.4 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Smol Llama 220M Bees Internal and how large is it?

Smol Llama 220M Bees Internal is developed by BEE-spoke-data, a model with 220m 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 Smol Llama 220M Bees Internal?

Smol Llama 220M Bees Internal is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Smol Llama 220M Bees Internal by BEE-spoke-data — VRAM 0.4GB, 2K context

Name: Smol Llama 220M Bees Internal
Author: BEE-spoke-data

Smol Llama 220M Bees Internal is an open-source language model by BEE-spoke-data. Features: 220m LLM, VRAM: 0.4GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.1.

Base model:bee-spoke-data/smol... Base model:finetune:bee-spoke-... Dataset:bee-spoke-data/bees-in... En Endpoints compatible Generated from trainer Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/BEE-spoke-data/smol_llama-220M-bees-internal

Smol Llama 220M Bees Internal Parameters and Internals

Model Type

text-generation

Additional Notes

The model fine-tuning involves various usage of hyperparameters such as a learning rate of 0.0001, training batch size of 4, and utilizes Adam Optimizer with specific betas (0.9,0.95) and epsilon (1e-08). Training proceeded with gradients accumulated every 8 steps, using a cosine learning rate scheduler with warmup ratio 0.05 for 2 epochs.

Supported Languages

en (high proficiency)

Training Details

Data Sources:

BEE-spoke-data/bees-internal

LLM Name	Smol Llama 220M Bees Internal
Repository 🤗	https://huggingface.co/BEE-spoke-data/smol_llama-220M-bees-internal
Base Model(s)	Smol Llama 220M GQA BEE-spoke-data/smol_llama-220M-GQA
Model Size	220m
Required VRAM	0.4 GB
Updated	2026-08-13
Maintainer	BEE-spoke-data
Model Type	llama
Model Files	0.4 GB 0.0 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32128
Torch Data Type	bfloat16

Rank the Smol Llama 220M Bees Internal 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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...l Llama 220M GQA 32K Theta Sft	32K / 0.4 GB	6	2
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Smol Llama 220M GQA	2K / 0.4 GB	326	13
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Note: green Score (e.g. "73.2") means that the model is better than BEE-spoke-data/smol_llama-220M-bees-internal.