Autotrain compatible Base model:finetune:h2oai/h2o-... Base model:h2oai/h2o-danube3-5... En Endpoints compatible Llama Pytorch Region:us Sft Trl Unsloth
Model Card on HF 🤗: https://huggingface.co/appvoid/massive
Massive Benchmarks
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)
Massive Parameters and Internals
| LLM Name | Massive |
| Repository 🤗 | https://huggingface.co/appvoid/massive |
| Base Model(s) | |
| Model Size | 500m |
| Required VRAM | 1 GB |
| Updated | 2024-12-22 |
| Maintainer | appvoid |
| Model Type | llama |
| Model Files | |
| Supported Languages | en |
| Model Architecture | LlamaForCausalLM |
| License | apache-2.0 |
| Context Length | 8192 |
| Model Max Length | 8192 |
| Transformers Version | 4.42.3 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <unk> |
| Vocabulary Size | 32000 |
| Torch Data Type | float16 |
Best Alternatives to Massive
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Text Arco | 8K / 1 GB | 171 | 0 |
| H2o Danube3 500M Chat | 8K / 1 GB | 6209 | 32 |
| H2o Danube3 500M Base | 8K / 1 GB | 2747 | 28 |
| Arco Plus | 8K / 1.6 GB | 137 | 6 |
| Danube Reasoner | 8K / 1 GB | 27 | 0 |
| Clite 500M | 8K / 1 GB | 70 | 3 |
| APT3 500M Base | 2K / 1.9 GB | 506 | 3 |
| ...ama 1.1B Textsql 500B 16layers | 2K / 2.2 GB | 0 | 0 |
| TIPO 500M | 2K / 1 GB | 4232 | 42 |
Note: green Score (e.g. "73.2") means that the model is better than appvoid/massive .
Rank the Massive Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217