Autotrain compatible Custom code Dataset:cerebras/slimpajama-62... Dataset:eleutherai/pile En Endpoints compatible Pytorch Region:us Rwkv5 Safetensors
V5 EagleX V2 7B HF 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)
V5 EagleX V2 7B HF Parameters and Internals
| LLM Name | V5 EagleX V2 7B HF |
| Repository 🤗 | https://huggingface.co/RWKV/v5-EagleX-v2-7B-HF |
| Model Size | 7b |
| Required VRAM | 15 GB |
| Updated | 2024-09-08 |
| Maintainer | RWKV |
| Model Type | rwkv5 |
| Model Files | |
| Supported Languages | en |
| Model Architecture | RwkvForCausalLM |
| License | apache-2.0 |
| Transformers Version | 4.34.0 |
| Tokenizer Class | RWKVWorldTokenizer |
| Vocabulary Size | 65536 |
Best Alternatives to V5 EagleX V2 7B HF
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| V5 Eagle 7B HF | 0K / 15 GB | 7296 | 70 |
| V5 EagleX 7B | 0K / 15 GB | 2 | 2 |
| Hermes RWKV V5 7B HF | 0K / 15 GB | 5 | 3 |
| V5 Eagle 7B 1 0T HF | 0K / 15 GB | 5 | 1 |
| Rwkv Raven 7B | 0K / 30.4 GB | 725 | 18 |
| Rwkv 4 7B Pile | 0K / 30.4 GB | 711 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than RWKV/v5-EagleX-v2-7B-HF .
Rank the V5 EagleX V2 7B HF Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803