johnsnowlabs/JSL-MedLlama-3-8B-v2.0
Full fine-tune vs meta-llama/Meta-Llama-3-8B. Fine-tune: 100% of the weights changed, across 32 of 32 layers.
Tensors changed: Embeddings 1/1, Norms 65/65, MLP 96/96, Attention 128/128, lm_head 1/1
6 derivatives checked
- featherless-ai-quants/johnsnowlabs-JSL-MedLlama-3-8B-v2.0-GGUF: Quantization
- mradermacher/JSL-MedLlama-3-8B-v2.0-i1-GGUF: Quantization
- mradermacher/JSL-MedLlama-3-8B-v2.0-GGUF: Same weights, converted
- tensorblock/JSL-MedLlama-3-8B-v2.0-GGUF: Quantization
- ChenWeiLi/MedLlama-3-8B_DARE: Full fine-tune
- ChenWeiLi/Med-ChimeraLlama-3-8B_SHERP: Full fine-tune
1 other repos hold byte-for-byte identical weight files.