Model Type |
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Additional Notes | The model uses bidirectional attention mechanisms and is trained on a vast multilingual text corpus. | |||||||
Input Output |
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LLM Name | Gte Qwen2 1.5B Instruct |
Repository ๐ค | https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct |
Model Size | 1.5b |
Required VRAM | 7.1 GB |
Updated | 2024-11-09 |
Maintainer | Alibaba-NLP |
Model Type | qwen2 |
Instruction-Based | Yes |
Model Files | |
Model Architecture | Qwen2ForCausalLM |
License | apache-2.0 |
Context Length | 131072 |
Model Max Length | 131072 |
Transformers Version | 4.41.2 |
Tokenizer Class | Qwen2Tokenizer |
Padding Token | <|endoftext|> |
Vocabulary Size | 151646 |
Torch Data Type | float32 |
Errors | replace |
Best Alternatives |
Context / RAM |
Downloads |
Likes |
---|---|---|---|
Replete Coder Qwen2 1.5B | 128K / 3.1 GB | 233 | 23 |
Samantha Qwen2 1.5B | 128K / 3.1 GB | 25 | 0 |
Qwen2.5 1.5B Instruct | 32K / 3.1 GB | 4731435 | 126 |
Qwen2 1.5B Instruct | 32K / 3.1 GB | 121922 | 131 |
Qwen2.5 Coder 1.5B Instruct | 32K / 3.1 GB | 18023 | 36 |
Qwen2 Chat Adamw Iter1 | 32K / 3.1 GB | 257 | 0 |
Qwen2 Coder Adamw Iter1 | 32K / 3.1 GB | 239 | 0 |
Chinese Text Correction 1.5B | 32K / 3.1 GB | 792 | 3 |
Qwen1 Chat Adamw Iter1 | 32K / 3.1 GB | 213 | 0 |
Qwen2.5 1.5B Instruct | 32K / 3.1 GB | 1676 | 1 |
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