Zephyr 220M Sft Full is an open-source language model by BEE-spoke-data. Features: 220m LLM, VRAM: 0.4GB, Context: 2K, License: apache-2.0, HF Score: 29.3, LLM Explorer Score: 0.18, Arc: 25.3, HellaSwag: 29, MMLU: 26.5, TruthfulQA: 43.2, WinoGrande: 51.6, GSM8K: 0.4.
Base model:bee-spoke-data/smol... Base model:finetune:bee-spoke-... Conversational Dataset:huggingfaceh4/ultracha... Endpoints compatible Generated from trainer Mistral Region:us Safetensors Tensorboard
Model Card on HF 🤗: https://huggingface.co/BEE-spoke-data/zephyr-220m-sft-full
Zephyr 220M Sft Full Benchmarks
ARC: 25.26 vs 96.7 (so35)-73.9%
HellaSwag: 29.03 vs 95.3 (gpt4)-69.5%
MMLU: 26.45 vs 88.3 (so35)-70%
TruthfulQA: 43.23 vs 59 (gpt4)-26.7%
WinoGrande: 51.62 vs 87.5 (gpt4)-41%
GSM8K: 0.38 vs 96.4 (so35)-99.6%
LLME Score: 0.17831
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)
Zephyr 220M Sft Full Parameters and Internals
| Training Details |
|
| LLM Name | Zephyr 220M Sft Full |
| Repository 🤗 | https://huggingface.co/BEE-spoke-data/zephyr-220m-sft-full |
| Base Model(s) | |
| Model Size | 220m |
| Required VRAM | 0.4 GB |
| Updated | 2026-03-15 |
| Maintainer | BEE-spoke-data |
| Model Type | mistral |
| Model Files | |
| Model Architecture | MistralForCausalLM |
| License | apache-2.0 |
| Context Length | 2048 |
| Model Max Length | 2048 |
| Transformers Version | 4.37.0.dev0 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <unk> |
| Vocabulary Size | 32128 |
| Torch Data Type | bfloat16 |
Best Alternatives to Zephyr 220M Sft Full
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Zephyr 220M DPO Full | 2K / 0.4 GB | 4 | 2 |
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Original data from HuggingFace, OpenCompass and various public git repos.
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Release v20241124