4-bit Autotrain compatible Conversational En Endpoints compatible Gptq Int4 Llama Pytorch Quantized Region:us Safetensors Yi1.5-9b-chat Zh
Model Card on HF 🤗: https://huggingface.co/modelscope/Yi-1.5-9B-Chat-GPTQ
Yi 1.5 9B Chat GPTQ 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)
Yi 1.5 9B Chat GPTQ Parameters and Internals
| Model Type |
| |
| Additional Notes |
| |
| Supported Languages |
|
| LLM Name | Yi 1.5 9B Chat GPTQ |
| Repository 🤗 | https://huggingface.co/modelscope/Yi-1.5-9B-Chat-GPTQ |
| Model Size | 9b |
| Required VRAM | 5.4 GB |
| Updated | 2025-02-22 |
| Maintainer | modelscope |
| Model Type | llama |
| Model Files | |
| GPTQ Quantization | Yes |
| Quantization Type | gptq |
| Model Architecture | LlamaForCausalLM |
| License | apache-2.0 |
| Context Length | 4096 |
| Model Max Length | 4096 |
| Transformers Version | 4.39.3 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <unk> |
| Vocabulary Size | 64000 |
| Torch Data Type | float16 |
Best Alternatives to Yi 1.5 9B Chat GPTQ
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Downloads |
Likes |
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| ...bit 128g Actorder False Marlin | 4K / 5.3 GB | 7 | 1 |
| Yi 9B 200K 6.0bpw H6 EXL2 | 256K / 7 GB | 5 | 1 |
| Yi 9B 200K 3.0bpw H6 EXL2 | 256K / 3.9 GB | 4 | 1 |
| Faro Yi 9B DPO 8bpw EXL2 | 32K / 8.3 GB | 13 | 1 |
| Faro Yi 9B DPO 6bpw EXL2 | 32K / 7 GB | 9 | 1 |
| Master Yi 9B 8.0bpw H8 EXL2 | 4K / 8.7 GB | 7 | 2 |
| Master Yi 9B 6.0bpw H6 EXL2 | 4K / 7 GB | 8 | 1 |
| Master Yi 9B 3.0bpw H6 EXL2 | 4K / 3.9 GB | 6 | 1 |
| Master Yi 9B 4.0bpw H6 EXL2 | 4K / 4.9 GB | 6 | 1 |
| Master Yi 9B 5.0bpw H6 EXL2 | 4K / 5.9 GB | 6 | 1 |
Note: green Score (e.g. "73.2") means that the model is better than modelscope/Yi-1.5-9B-Chat-GPTQ .
Rank the Yi 1.5 9B Chat GPTQ Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227