tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.5
Full fine-tune vs tokyotech-llm/Llama-3.1-Swallow-8B-v0.5. Fine-tune: 100% of the weights changed, across 32 of 32 layers.
Tensors changed: Embeddings 1/1, Norms 64/65, MLP 96/96, Attention 128/128, lm_head 1/1
11 derivatives checked
- mmnga/Llama-3.1-Swallow-8B-Instruct-v0.5-gguf: Quantization
- mradermacher/Llama-3.1-Swallow-8B-Instruct-v0.5-i1-GGUF: Quantization
- mradermacher/Llama-3.1-Swallow-8B-Instruct-v0.5-GGUF: Same weights, converted
- simaai/Llama-3.1-Swallow-8B-Instruct-v0.5-GPTQ-Safetensors: Quantization
- marcelone/Llama-3.1-Swallow-8B-Instruct-v0.5-gguf: Same weights, converted
- neody/Llama-3.1-Swallow-8B-Instruct-v0.5-gguf: Same weights, converted
- tensorblock/tokyotech-llm_Llama-3.1-Swallow-8B-Instruct-v0.5-GGUF: Quantization
- DataPilot/ArrowCanaria-Llama-8B-SFT-v0.1: Full fine-tune
- mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.5-4bit: Quantization
- vericava/Llama-3.1-Swallow-8B-Instruct-v0.5-tooled: Full fine-tune
- sociocom/MedPHINER-Llama-3.1-Swallow-8B-Instruct-v0.5: LoRA-style