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Model: canbingol/gemma3_1B_base-tr-cpt-1epoch_stage1 Source: Original Platform
2026-05-31 13:21:17 +08:00
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--- a/README.md
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+---
+library_name: transformers
+tags:
+- trl
+- cpt
+datasets:
+- canbingol/vngrs-web-corpus-200k
+language:
+- tr
+- en
+base_model:
+- google/gemma-3-1b-pt
+new_version: canbingol/gemma3_1B_base-tr-cpt-2nd_epoch_stage1
+---
+
+# Model Card: Gemma3-1B Turkish CPT (50K Subset, 1 Epoch – Stage 1)
+
+## Overview
+
+This model is a Turkish Continued Pretraining (CPT) variant of `google/gemma-3-1b-pt`.
+
+The base model was further trained for **1 epoch** on the first **50,000 samples** of a Turkish web corpus.  
+This stage represents a broader data exposure regime compared to small-subset experiments and aims to improve:
+
+- Turkish fluency
+- Vocabulary coverage
+- Domain familiarity
+- Statistical adaptation to Turkish web distribution
+
+This release corresponds to **Stage 1** of a multi-stage CPT pipeline and is intended for research and experimental analysis.
+
+---
+
+## Base Model
+
+- `google/gemma-3-1b-pt`
+
+---
+
+## Training Setup
+
+- Dataset: `canbingol/vngrs-web-corpus-200k`
+- Subset Used: First 50,000 samples
+- Training Objective: Continued Pretraining 
+- Epochs: 1
+- Data Regime: Plain text 
+- Token Count (approximate): ~21.5M tokens
+
+---
+
+
+## Usage Example
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "canbingol/gemma3_1B_base-tr-cpt-1epoch_stage1"
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+model = AutoModelForCausalLM.from_pretrained(model_id)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+model = model.to(device)
+
+prompt = "bundan böyle"
+inputs = tokenizer(prompt, return_tensors="pt").to(device)
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=50,
+    do_sample=True,
+    temperature=0.8,
+    top_p=0.9
+)
+
+generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(generated_text)
--- a/config.json
+++ b/config.json
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+{
+  "_sliding_window_pattern": 6,
+  "architectures": [
+    "Gemma3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": null,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "dtype": "bfloat16",
+  "eos_token_id": 1,
+  "final_logit_softcapping": null,
+  "head_dim": 256,
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 1152,
+  "initializer_range": 0.02,
+  "intermediate_size": 6912,
+  "layer_types": [
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention"
+  ],
+  "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_parameters": {
+    "full_attention": {
+      "rope_theta": 1000000,
+      "rope_type": "default"
+    },
+    "sliding_attention": {
+      "rope_theta": 10000,
+      "rope_type": "default"
+    }
+  },
+  "sliding_window": 512,
+  "sliding_window_pattern": 6,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.2.0",
+  "use_bidirectional_attention": false,
+  "use_cache": false,
+  "vocab_size": 262144
+}
--- a/generation_config.json
+++ b/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": "5.2.0"
+}
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--- a/tokenizer_config.json
+++ b/tokenizer_config.json
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+{
+  "backend": "tokenizers",
+  "boi_token": "<start_of_image>",
+  "bos_token": "<bos>",
+  "clean_up_tokenization_spaces": false,
+  "eoi_token": "<end_of_image>",
+  "eos_token": "<eos>",
+  "image_token": "<image_soft_token>",
+  "is_local": false,
+  "mask_token": "<mask>",
+  "model_max_length": 1000000000000000019884624838656,
+  "model_specific_special_tokens": {
+    "boi_token": "<start_of_image>",
+    "eoi_token": "<end_of_image>",
+    "image_token": "<image_soft_token>"
+  },
+  "pad_token": "<pad>",
+  "sp_model_kwargs": null,
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}