Arxiv:2303.08774 6-bit Autotrain compatible Conversational Dataset:argilla/ultrafeedback-... Dataset:intel/orca dpo pairs Dataset:jondurbin/truthy-dpo-v... Dataset:wenbopan/chinese-dpo-p... En Endpoints compatible Exl2 Llama Quantized Region:us Safetensors Zh
Faro Yi 9B DPO 6bpw EXL2 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)
Faro Yi 9B DPO 6bpw EXL2 Parameters and Internals
| LLM Name | Faro Yi 9B DPO 6bpw EXL2 |
| Repository 🤗 | https://huggingface.co/vikarti-anatra/Faro-Yi-9B-DPO-6bpw-exl2 |
| Model Size | 9b |
| Required VRAM | 7 GB |
| Updated | 2024-10-17 |
| Maintainer | vikarti-anatra |
| Model Type | llama |
| Model Files | |
| Supported Languages | en zh |
| Quantization Type | exl2 |
| Model Architecture | LlamaForCausalLM |
| License | mit |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.39.3 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <unk> |
| Vocabulary Size | 64000 |
| Torch Data Type | bfloat16 |
Best Alternatives to Faro Yi 9B DPO 6bpw EXL2
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Yi 9B 200K 3.0bpw H6 EXL2 | 256K / 3.9 GB | 4 | 1 |
| Yi 9B 200K 6.0bpw H6 EXL2 | 256K / 7 GB | 0 | 1 |
| Faro Yi 9B DPO 8bpw EXL2 | 32K / 8.3 GB | 13 | 1 |
| Master Yi 9B 8.0bpw H8 EXL2 | 4K / 8.7 GB | 7 | 2 |
| Master Yi 9B 6.0bpw H6 EXL2 | 4K / 7 GB | 11 | 1 |
| Master Yi 9B 5.0bpw H6 EXL2 | 4K / 5.9 GB | 10 | 1 |
| Master Yi 9B 3.0bpw H6 EXL2 | 4K / 3.9 GB | 4 | 1 |
| Master Yi 9B 4.0bpw H6 EXL2 | 4K / 4.9 GB | 4 | 1 |
| Yi 1.5 9B 8bit | 4K / 9.3 GB | 4 | 1 |
| Yi 9B 200K | 256K / 17.7 GB | 9042 | 75 |
Note: green Score (e.g. "73.2") means that the model is better than vikarti-anatra/Faro-Yi-9B-DPO-6bpw-exl2 .
Rank the Faro Yi 9B DPO 6bpw EXL2 Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803