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Model: srs6901/Vikras-MixP
Source: Original Platform

Vikra-HCT-YeAM-PhiMma-1B/README.md

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+---
+license: gemma
+library_name: transformers
+pipeline_tag: text-generation
+base_model: google/gemma-3-1b-pt
+---
+
+# Vikra-HCT-YeAM-PhiMma-1B
+Gemma-3-1b-pt + Microsoft_phi-2
+HCT architecture release. YeAM (Yet Another Merge) implementation invariant.
+
+## What it is
+
+A compact 1B-class model produced via HCT-compatible merging.
+The checkpoint is published in standard Hugging Face format (safetensors + index).
+
+## YeAM summary
+
+YeAM performs a controlled merge in a real 4D geometric formulation with ray-intersection alignment in parameter space.
+It also supports targeted knowledge injection (distillation-style) into a chosen model while remaining HF-compatible.
+
+## Usage (Transformers)
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+m = "/path/to/Vikra-HCT-YeAM-PhiMma-1B"
+
+tok = AutoTokenizer.from_pretrained(m, use_fast=False)
+model = AutoModelForCausalLM.from_pretrained(
+    m,
+    torch_dtype=torch.bfloat16,
+    device_map="cuda",
+).eval()
+
+inputs = tok("Hello!", return_tensors="pt").to(model.device)
+out = model.generate(**inputs, max_new_tokens=128)
+print(tok.decode(out[0], skip_special_tokens=True))
+```
+
+## GGUF
+
+Convert and quantize with llama.cpp (example):
+
+```bash
+python3 /path/to/llama.cpp/convert_hf_to_gguf.py /path/to/model --outtype bf16 --outfile model.bf16.gguf
+/path/to/llama.cpp/build/bin/llama-quantize model.bf16.gguf model.Q6_K.gguf Q6_K
+```

Vikra-HCT-YeAM-PhiMma-1B/added_tokens.json

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+{
+  "<image_soft_token>": 262144
+}

Vikra-HCT-YeAM-PhiMma-1B/config.json

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+{
+  "architectures": [
+    "Gemma3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": null,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "eos_token_id": [
+    1,
+    106
+  ],
+  "final_logit_softcapping": null,
+  "head_dim": 256,
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 1152,
+  "initializer_range": 0.02,
+  "intermediate_size": 6912,
+  "max_position_embeddings": 32768,
+  "model_type": "gemma3_text",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 26,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_local_base_freq": 10000,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": 512,
+  "sliding_window_pattern": 6,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.50.0.dev0",
+  "use_cache": true,
+  "vocab_size": 262144
+}

Vikra-HCT-YeAM-PhiMma-1B/generation_config.json

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+{
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "do_sample": true,
+  "eos_token_id": [
+    1,
+    106
+  ],
+  "pad_token_id": 0,
+  "top_k": 64,
+  "top_p": 0.95,
+  "transformers_version": "4.50.0.dev0"
+}

Vikra-HCT-YeAM-PhiMma-1B/model-00001-of-00002.safetensors

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+oid sha256:cd10088d6f4ea7bd681d61f3ae77b02e6202587e0817b5d91dad2e949bf248b7
+size 1081244120

Vikra-HCT-YeAM-PhiMma-1B/model-00002-of-00002.safetensors

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Vikra-HCT-YeAM-PhiMma-1B/special_tokens_map.json

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+{
+  "boi_token": "<start_of_image>",
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eoi_token": "<end_of_image>",
+  "eos_token": {
+    "content": "<eos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "image_token": "<image_soft_token>",
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

Vikra-HCT-YeAM-PhiMma-1B/tokenizer.json

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+size 33384568

Vikra-HCT-YeAM-PhiMma-1B/tokenizer.model

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