Model Card on HF 🤗: https://huggingface.co/Lazycuber/pyg-instruct-wizardlm
Pyg Instruct Wizardlm Benchmarks
ARC: 40.96 vs 96.7 (so35)-57.6%
HellaSwag: 66.71 vs 95.3 (gpt4)-30%
MMLU: 26.33 vs 88.3 (so35)-70.2%
TruthfulQA: 31.93 vs 59 (gpt4)-45.9%
WinoGrande: 63.69 vs 87.5 (gpt4)-27.2%
GSM8K: 1.59 vs 96.4 (so35)-98.4%
LLME Score: 0.16528
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)
Pyg Instruct Wizardlm Parameters and Internals
| LLM Name | Pyg Instruct Wizardlm |
| Repository 🤗 | https://huggingface.co/Lazycuber/pyg-instruct-wizardlm |
| Model Size | 6b |
| Required VRAM | 12.2 GB |
| Updated | 2025-02-05 |
| Maintainer | Lazycuber |
| Model Type | gptj |
| Instruction-Based | Yes |
| Model Files | |
| Model Architecture | GPTJForCausalLM |
| Model Max Length | 1024 |
| Transformers Version | 4.28.1 |
| Tokenizer Class | GPT2Tokenizer |
| Beginning of Sentence Token | <|endoftext|> |
| End of Sentence Token | <|endoftext|> |
| Unk Token | <|endoftext|> |
| Vocabulary Size | 50402 |
| Torch Data Type | bfloat16 |
| Activation Function | gelu_new |
| Errors | replace |
Best Alternatives to Pyg Instruct Wizardlm
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| GPT J 6B Alpaca Gpt4 | 0K / 24.3 GB | 8 | 20 |
| Zenos GPT J 6B Instruct 4bit | 0K / 3.4 GB | 146 | 1 |
Rank the Pyg Instruct Wizardlm Capabilities
🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟
What open-source LLMs or SLMs are you in search of? 42577 in total.
Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227