Model Card on HF 🤗: https://huggingface.co/Narednra/Meditron_llama2_7b_58k-AWQ
Meditron Llama2 7b 58k AWQ 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)
Meditron Llama2 7B 58K AWQ Parameters and Internals
| LLM Name | Meditron Llama2 7b 58k AWQ |
| Repository 🤗 | https://huggingface.co/Narednra/Meditron_llama2_7b_58k-AWQ |
| Model Size | 7b |
| Required VRAM | 3.9 GB |
| Updated | 2025-02-22 |
| Maintainer | Narednra |
| Model Type | llama |
| Model Files | |
| AWQ Quantization | Yes |
| Quantization Type | awq |
| Model Architecture | LlamaForCausalLM |
| Context Length | 2048 |
| Model Max Length | 2048 |
| Transformers Version | 4.38.2 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <PAD> |
| Vocabulary Size | 32017 |
| Torch Data Type | float16 |
Best Alternatives to Meditron Llama2 7B 58K AWQ
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Smaugv0.1 AWQ | 195K / 19.3 GB | 5 | 1 |
| Yarn Llama 2 7B 64K AWQ | 64K / 3.9 GB | 116 | 0 |
| Calm2 7B Chat AWQ | 32K / 4.4 GB | 102 | 2 |
| Llama 2 7B 32K Instruct AWQ | 32K / 3.9 GB | 93 | 2 |
| ... SWE Llama 7B Updated 4bit AWQ | 16K / 3.9 GB | 80 | 0 |
| ...Llama 7B Python Hf W4 G128 AWQ | 16K / 3.9 GB | 4148 | 0 |
| Pandalyst 7B V1.2 AWQ | 16K / 3.9 GB | 80 | 1 |
| Tora Code 7B V1.0 AWQ | 16K / 3.9 GB | 79 | 0 |
| ...eechless Tora Code 7B V1.0 AWQ | 16K / 3.9 GB | 77 | 1 |
| Pandalyst 7B V1.1 AWQ | 16K / 3.9 GB | 79 | 1 |
Note: green Score (e.g. "73.2") means that the model is better than Narednra/Meditron_llama2_7b_58k-AWQ .
Rank the Meditron Llama2 7B 58K AWQ Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227