Model Card on HF 🤗: https://huggingface.co/GritLM/emb_m7_nodes16_fast
Emb M7 Nodes16 Fast 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)
Emb M7 Nodes16 Fast Parameters and Internals
| LLM Name | Emb M7 Nodes16 Fast |
| Repository 🤗 | https://huggingface.co/GritLM/emb_m7_nodes16_fast |
| Model Size | 7b |
| Required VRAM | 14.2 GB |
| Updated | 2025-10-17 |
| Maintainer | GritLM |
| Model Type | mistral |
| Model Files | |
| Model Architecture | MistralForCausalLM |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.36.2 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <s> |
| Vocabulary Size | 32000 |
| Torch Data Type | bfloat16 |
Best Alternatives to Emb M7 Nodes16 Fast
Best Alternatives |
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Likes |
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| ...Nemo Instruct 2407 Abliterated | 1000K / 24.5 GB | 141 | 18 |
| MegaBeam Mistral 7B 512K | 512K / 14.4 GB | 8908 | 50 |
| SpydazWeb AI HumanAI RP | 512K / 14.4 GB | 17 | 1 |
| SpydazWeb AI HumanAI 002 | 512K / 14.4 GB | 18 | 1 |
| ...daz Web AI ChatML 512K Project | 512K / 14.5 GB | 12 | 0 |
| MegaBeam Mistral 7B 300K | 282K / 14.4 GB | 3779 | 16 |
| MegaBeam Mistral 7B 300K | 282K / 14.4 GB | 8082 | 16 |
| Hebrew Mistral 7B 200K | 256K / 30 GB | 1316 | 15 |
| Astral 256K 7B V2 | 250K / 14.4 GB | 5 | 0 |
| Astral 256K 7B | 250K / 14.4 GB | 5 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than GritLM/emb_m7_nodes16_fast .
Rank the Emb M7 Nodes16 Fast Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124