Autotrain compatible Custom code Dataset:vikp/reverse instruct Endpoints compatible Instruct Llama Pytorch Region:us Sharded
Reverse Instruct 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)
Reverse Instruct Parameters and Internals
| LLM Name | Reverse Instruct |
| Repository 🤗 | https://huggingface.co/vikp/reverse_instruct |
| Required VRAM | 27 GB |
| Updated | 2024-10-18 |
| Maintainer | vikp |
| Model Type | llama |
| Instruction-Based | Yes |
| Model Files | |
| Model Architecture | LlamaForCausalLM |
| License | cc |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.31.0 |
| Tokenizer Class | LlamaTokenizer |
| Beginning of Sentence Token | <s> |
| End of Sentence Token | </s> |
| Unk Token | <unk> |
| Vocabulary Size | 32001 |
| Torch Data Type | float32 |
Best Alternatives to Reverse Instruct
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| FATLLAMA 1.7T Instruct | 128K / 438.9 GB | 23 | 3 |
| Etri Ones Solar | 4K / 42.9 GB | 58 | 0 |
| Law Chat | 4K / 27 GB | 1155 | 33 |
| Phi 3 Orpo V8.16 | 4K / 7.6 GB | 8 | 0 |
| Small Instruct | 4K / 2.9 GB | 4139 | 1 |
| Tinyllama Python | 4K / 2.2 GB | 7 | 1 |
| Model 007 Preview | 4K / 138 GB | 63 | 1 |
| Taiwan LLaMa V0.0 | 4K / 26 GB | 9 | 1 |
| Taiwan LLaMa V0.9 | 4K / 26 GB | 11 | 0 |
| Kolong Llama V0.1 | 2K / 13.7 GB | 4089 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than vikp/reverse_instruct .
Rank the Reverse Instruct Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803