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Model: wvnvwn/Meta-Llama-3-8B-Instruct-fedavg-v0
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+pipeline_tag: text-generation
+base_model:
+- meta-llama/Meta-Llama-3-8B-Instruct
+tags:
+- peft
+- lora
+- merged
+---
+# Meta-Llama-3-8B-Instruct-fedavg-v0
+
+This repository contains a full merged model produced by applying a PEFT LoRA adapter to its base model. It is intended for reproducible evaluation without requiring a separate adapter loading path.
+
+## Quick Start
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "wvnvwn/Meta-Llama-3-8B-Instruct-fedavg-v0"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+```
+
+Run the bundled FSL evaluation wrapper:
+
+```bash
+bash fsl/src/evaluation/overall_eval.sh \
+    --model_name wvnvwn/Meta-Llama-3-8B-Instruct-fedavg-v0 \
+    --model_type instruct \
+    --max_samples 100 \
+    --output_root fsl/results/evaluation/Meta-Llama-3-8B-Instruct-fedavg-v0
+```
+
+## Training Procedure
+
+- Procedure: Federated LoRA fine-tuning followed by adapter aggregation. The resulting PEFT LoRA adapter was merged into the base model for reproducible evaluation.
+- Algorithm: `fedavg`
+- Training data: `data_hetero_with_4_tasks`
+- Number of clients: `8`
+- Communication round/checkpoint: `3`
+- Local epochs: `3`
+- Local batch size: `256`
+- Local micro batch size: `16`
+- Local learning rate: `0.0003`
+
+Original training command:
+
+Not specified
+
+## Merge Metadata
+
+- Base model: `meta-llama/Meta-Llama-3-8B-Instruct`
+- Adapter source: `/NHNHOME/0226010080_A/BASE/jongbokwon/FLS/fsl/outputs/fedavg/8/2`
+- PEFT type: `LORA`
+- Task type: `CAUSAL_LM`
+- LoRA rank: `16`
+- LoRA alpha: `16`
+- Target modules: `up_proj`, `v_proj`, `gate_proj`, `q_proj`, `k_proj`, `o_proj`, `down_proj`
+- Merged at UTC: `2026-05-22T05:24:31.213169+00:00`
+
+## Framework Versions
+
+- python: `3.10.20`
+- platform: `Linux-6.8.0-100-generic-x86_64-with-glibc2.39`
+- torch: `2.11.0+cu130`
+- cuda: `13.0`
+- transformers: `4.57.1`
+- peft: `0.19.1`
+- accelerate: `1.13.0`
+- huggingface_hub: `0.36.2`
+- safetensors: `0.7.0`
+- vllm: `0.20.2`
+- wandb: `0.27.0`
+
+## Notes
+
+- This is a merged full-weight model, not an adapter-only checkpoint.
+- Redistribution/access should follow the base model license and access policy.
+- `merge_info.json` in this repository records the adapter and merge configuration.

chat_template.jinja

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+{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
+
+'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
+
+' }}{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "dtype": "bfloat16",
+  "eos_token_id": 128009,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.1",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128009
+  ],
+  "max_length": 4096,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.57.1"
+}

merge_info.json

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+{
+  "adapter_dir": "/NHNHOME/0226010080_A/BASE/jongbokwon/FLS/fsl/outputs/fedavg/8/2",
+  "base_model": "meta-llama/Meta-Llama-3-8B-Instruct",
+  "peft_type": "LORA",
+  "task_type": "CAUSAL_LM",
+  "lora_r": 16,
+  "lora_alpha": 16,
+  "target_modules": [
+    "up_proj",
+    "v_proj",
+    "gate_proj",
+    "q_proj",
+    "k_proj",
+    "o_proj",
+    "down_proj"
+  ],
+  "merged_at_utc": "2026-05-22T05:24:31.213169+00:00",
+  "output_dir": "/NHNHOME/0226010080_A/BASE/jongbokwon/FLS/fsl/outputs/fedavg/8/merged",
+  "repo_id": "wvnvwn/Meta-Llama-3-8B-Instruct-fedavg-v0",
+  "private": false,
+  "revision": null,
+  "dtype": "bfloat16",
+  "max_shard_size": "5GB",
+  "training": {
+    "procedure": "Federated LoRA fine-tuning followed by adapter aggregation. The resulting PEFT LoRA adapter was merged into the base model for reproducible evaluation.",
+    "algorithm": "fedavg",
+    "training_data": "data_hetero_with_4_tasks",
+    "training_command": null,
+    "num_clients": 8,
+    "communication_round": "3",
+    "local_epochs": "3",
+    "local_batch_size": "256",
+    "local_micro_batch_size": "16",
+    "local_learning_rate": "0.0003"
+  },
+  "framework_versions": {
+    "python": "3.10.20",
+    "platform": "Linux-6.8.0-100-generic-x86_64-with-glibc2.39",
+    "torch": "2.11.0+cu130",
+    "cuda": "13.0",
+    "transformers": "4.57.1",
+    "peft": "0.19.1",
+    "accelerate": "1.13.0",
+    "huggingface_hub": "0.36.2",
+    "safetensors": "0.7.0",
+    "vllm": "0.20.2",
+    "wandb": "0.27.0"
+  }
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