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config.json

@@ -1,76 +1,3 @@
-{
-  "_name_or_path": "NER-Standard",
-  "architectures": ["LlamaForCausalLM"],
-  "vocab_size": 49152,
-  "context_length": 2048,
-  "hidden_size": 576,
-  "num_attention_heads": 9,
-  "num_hidden_layers": 30,
-  "intermediate_size": 1536,
-  "quantization_config": {
-    "quant_method": "gguf",
-    "quantization_type": "Q8_0",
-    "quantization_bits": 8,
-    "compression_ratio": 0.5,
-    "quantization_version": "2",
-    "quantization_fidelity": "high",
-    "quantization_format": "GGUF",
-    "quantization_description": "8-bit quantization with optimized weights for high fidelity"
-  },
-  "file_size": 143025408,
-  "file_size_mb": 143,
-  "gguf_file": "model.gguf",
-  "model_family": "llama",
-  "model_version": "1.0.0",
-  "hardware_requirements": {
-    "minimum_ram": "8GB",
-    "recommended_ram": "16GB",
-    "cpu_compatibility": "Any modern CPU",
-    "gpu_compatibility": {
-      "nvidia": "Any CUDA-compatible GPU",
-      "amd": "Any ROCm-compatible GPU",
-      "apple_silicon": "M1/M2/M3/M4 chips with Metal"
-    },
-    "os_compatibility": ["linux", "macos", "windows"],
-    "recommended_hardware": "Apple Silicon M2/M3/M4, Intel i7/i9, or NVIDIA RTX 30-series",
-    "memory_usage_estimate": "~2GB during inference",
-    "storage_requirements": "150MB free space"
-  },
-  "performance_metrics": {
-    "ner_f1_score": 0.951,
-    "precision": 0.915,
-    "recall": 1.000,
-    "entity_types_supported": ["PERSON", "ORG", "LOC", "MISC"],
-    "latency_ms": 323.3,
-    "throughput_requests_per_second": 3.1,
-    "benchmark_dataset": "NER Benchmark Dataset",
-    "benchmark_samples": 100,
-    "evaluation_date": "2025-10-07"
-  },
-  "model_creator": "Minibase AI",
-  "model_url": "https://minibase.ai",
-  "discord_url": "https://discord.com/invite/BrJn4D2Guh",
-    "repository_url": "https://github.com/minibase-ai/ner-standard",
-    "paper_url": "https://minibase.ai/research/ner-standard",
-  "license": "apache-2.0",
-  "tags": [
-    "text-generation",
-    "named-entity-recognition",
-    "ner",
-    "nlp",
-    "information-extraction",
-    "person",
-    "organization",
-    "location",
-    "miscellaneous",
-    "llama",
-    "gguf",
-    "quantized",
-    "cpu-inference",
-    "apple-silicon",
-    "minibase",
-    "standard-model",
-    "2048-context",
-    "q8_0"
-  ]
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:904a63de9bd60dc95f16a0f5518acf7c8249782849c95724962a3af937dac700
+size 2258