Autotrain compatible Endpoints compatible Generated from trainer Gpt neox Instruct Pytorch Region:us
Model Card on HF 🤗: https://huggingface.co/Multi-Domain-Expert-Learning/expert-min-pile-instruct
Expert Min Pile 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)
Expert Min Pile Instruct Parameters and Internals
| Model Type |
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| Additional Notes |
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| Training Details |
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| LLM Name | Expert Min Pile Instruct |
| Repository 🤗 | https://huggingface.co/Multi-Domain-Expert-Learning/expert-min-pile-instruct |
| Model Size | 1b |
| Required VRAM | 2.1 GB |
| Updated | 2025-02-22 |
| Maintainer | Multi-Domain-Expert-Learning |
| Model Type | gpt_neox |
| Instruction-Based | Yes |
| Model Files | |
| Model Architecture | GPTNeoXForCausalLM |
| Context Length | 2048 |
| Model Max Length | 2048 |
| Transformers Version | 4.28.1 |
| Tokenizer Class | GPTNeoXTokenizer |
| Vocabulary Size | 50279 |
| Torch Data Type | float16 |
Best Alternatives to Expert Min Pile Instruct
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| ...hia 1B Deduped Instruct Ckpt 1 | 2K / 2.1 GB | 60 | 0 |
| ...hia 1B Deduped Instruct Ckpt 2 | 2K / 2.1 GB | 59 | 0 |
| B1ade 1B | 2K / 2 GB | 1982 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than Multi-Domain-Expert-Learning/expert-min-pile-instruct .
Rank the Expert Min Pile Instruct Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227