Arxiv:1910.09700 4-bit Autotrain compatible Bitsandbytes Endpoints compatible Recurrent gemma Region:us Safetensors Sharded Tensorflow
Model Card on HF 🤗: https://huggingface.co/QuantiPhy/google-recurrentgemma-9b-4Q
Google Recurrentgemma 9B 4Q 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)
Google Recurrentgemma 9B 4Q Parameters and Internals
| LLM Name | Google Recurrentgemma 9B 4Q |
| Repository 🤗 | https://huggingface.co/QuantiPhy/google-recurrentgemma-9b-4Q |
| Model Size | 9b |
| Required VRAM | 6.1 GB |
| Updated | 2025-02-05 |
| Maintainer | QuantiPhy |
| Model Type | recurrent_gemma |
| Model Files | |
| Model Architecture | RecurrentGemmaForCausalLM |
| Transformers Version | 4.42.0.dev0 |
| Vocabulary Size | 256000 |
| Torch Data Type | bfloat16 |
Best Alternatives to Google Recurrentgemma 9B 4Q
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Recurrentgemma 9B It | 0K / 19.3 GB | 9741 | 50 |
| Recurrentgemma 9B | 0K / 19.3 GB | 152 | 58 |
| Recurrentgemma 9B It | 0K / 19.3 GB | 6 | 3 |
| Recurrentgemma 9B | 0K / 19.3 GB | 8 | 1 |
| Recurrentgemma 9B It Bnb 4bit | 0K / 6.4 GB | 10 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than QuantiPhy/google-recurrentgemma-9b-4Q .
Rank the Google Recurrentgemma 9B 4Q Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227