Autotrain compatible Conversational Dataset:0-hero/matter-0.2 En Endpoints compatible Mistral Pytorch Region:us Safetensors
Matter 0.2 7B Benchmarks
ARC: 61.6-36%
HellaSwag: 82.39-13.5%
MMLU: 62.51-27.7%
TruthfulQA: 48.11-18.5%
WinoGrande: 79.48-9.2%
GSM8K: 53.9-41.4%
nn.n% — How the model compares to the GPT-4.
Matter 0.2 7B Parameters and Internals
| LLM Name | Matter 0.2 7B |
| Repository | Open on 🤗 |
| Model Size | 7b |
| Required VRAM | 14.5 GB |
| Updated | 2024-07-27 |
| Maintainer | 0-hero |
| Model Type | mistral |
| Model Files | |
| Supported Languages | en |
| Model Architecture | MistralForCausalLM |
| License | apache-2.0 |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.40.0.dev0 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | </s> |
| Vocabulary Size | 32006 |
| Torch Data Type | bfloat16 |
Best Alternatives to Matter 0.2 7B
Best Alternatives |
HF Rank |
Context/RAM |
Downloads |
Likes |
|---|---|---|---|---|
| MegaBeam Mistral 7B 300K | 0.3 | 282K / 14.4 GB | 2057 | 15 |
| Hebrew Mistral 7B 200K | 0.3 | 256K / 30 GB | 2091 | 15 |
| Astral 256K 7B V2 | 0.2 | 250K / 14.4 GB | 239 | 0 |
| Astral 256K 7B | 0.2 | 250K / 14.4 GB | 233 | 0 |
| Buddhi 128K Chat 7B | 0.3 | 128K / 14.4 GB | 612 | 14 |
| LuminRP 7B 128K V0.2 | 0.3 | 128K / 14.4 GB | 261 | 0 |
| ...1 Summarize 64K LoRANET Merged | 0.2 | 128K / 14.4 GB | 232 | 0 |
| ... Summarize 64K QLoRANET Merged | 0.2 | 128K / 4.1 GB | 8 | 0 |
| LuminRP 7B 128K V0.5 | 0.2 | 128K / 14.5 GB | 9 | 1 |
| LuminRP 7B 128K V0.4 | 0.2 | 128K / 14.4 GB | 12 | 1 |
Note: green Score (e.g. "73.2") means that the model is better than 0-hero/Matter-0.2-7B .
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072501