4-bit Autotrain compatible Awq Base model:quantized:whiterabb... Base model:whiterabbitneo/whit... Llama Quantized Region:us Safetensors Sharded Tensorflow
WhiteRabbitNeo 33B V1 AWQ 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)
WhiteRabbitNeo 33B V1 AWQ Parameters and Internals
| LLM Name | WhiteRabbitNeo 33B V1 AWQ |
| Repository 🤗 | https://huggingface.co/TheBloke/WhiteRabbitNeo-33B-v1-AWQ |
| Model Name | WhiteRabbitNeo 33B v1 |
| Model Creator | WhiteRabbitNeo |
| Base Model(s) | |
| Model Size | 33b |
| Required VRAM | 18.1 GB |
| Updated | 2024-09-16 |
| Maintainer | TheBloke |
| Model Type | deepseek |
| Model Files | |
| AWQ Quantization | Yes |
| Quantization Type | awq |
| Model Architecture | LlamaForCausalLM |
| License | other |
| Context Length | 16384 |
| Model Max Length | 16384 |
| Transformers Version | 4.36.2 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <｜end▁of▁sentence｜> |
| Vocabulary Size | 32256 |
| Torch Data Type | float16 |
Best Alternatives to WhiteRabbitNeo 33B V1 AWQ
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| ...eepseek Coder 33B Instruct AWQ | 16K / 18.1 GB | 82567 | 35 |
| Everyone Coder 33B Base AWQ | 16K / 18.1 GB | 10 | 2 |
| WizardCoder 33B V1.1 AWQ | 16K / 18.1 GB | 40 | 5 |
| Deepseek Coder 33B Base AWQ | 16K / 18.1 GB | 62 | 4 |
| Code 33B AWQ | 2K / 17.6 GB | 14 | 3 |
| Python Code 33B AWQ | 2K / 17.6 GB | 13 | 1 |
| Vicuna 33B Coder AWQ | 2K / 17.6 GB | 21 | 1 |
| Vicuna 33B AWQ | 2K / 17.6 GB | 20 | 2 |
| Fin Llama 33B AWQ | 2K / 17.6 GB | 19 | 4 |
| Chronoboros 33B AWQ | 2K / 17.6 GB | 23 | 2 |
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/WhiteRabbitNeo-33B-v1-AWQ .
Rank the WhiteRabbitNeo 33B V1 AWQ Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803