Upload LlamaForCausalLM

README.md

@@ -1,81 +1,3 @@
----
-license: mit
-datasets:
-- aerdincdal/CBDDO-LLM-DB-V1
-language:
-- tr
-metrics:
-- accuracy
-- bertscore
-- bleu
-- bleurt
-- brier_score
-- cer
-- character
-- charcut_mt
-- chrf
-- code_eval
----
-
-## LLama3 Tabanlı Türkçe Dil Modeli: aerdincdal/CBDDO-LLM-8B-Instruct-v1
-
-**aerdincdal/CBDDO-LLM-8B-Instruct-v1** Türkçe dil modeli, güçlü LLama3 mimarisine dayanarak 1.5 milyon satırlık veri kümesi kullanılarak Instruction Tune yöntemi ile özenle eğitilmiştir. Bu model, doğal dil işleme alanındaki çeşitli görevleri başarıyla yerine getirebilmek için tasarlanmıştır ve kullanımı son derece pratiktir.
-
-### Modelin Başlıca Özellikleri
-
-- **Yenilikçi LLama3 Mimarisi:** Yüksek performans sunan ve doğal dil işlemeye yeni bir soluk getiren bu mimari, modelin Türkçe'nin dilbilgisini ve sentaksını derinlemesine anlamasını sağlar.
-- **Kapsamlı Veri Kümesi:** Instruction Tune yöntemi ile eğitilmiş bu geniş veri kümesi, modelin Türkçe metinler üretme konusunda akıcılık ve doğruluk kazanmasına imkan tanır.
-- **Çok Yönlülük ve Esneklik:** Metin oluşturma, çeviri, soru-cevaplama, özetleme ve kod yazma gibi çeşitli görevlerde etkili performans sergiler.
-
-### Modeli Kullanmaya Başlama
-
-Modeli kullanmaya başlamak için aşağıdaki adımları takip edebilirsiniz:
-
-1. **Gerekli Kütüphaneleri Yükleyin:**
-   ```bash
-   pip install transformers
-   ```
-
-2. **Modeli Test Edin:**
-   Python script'ini kullanarak modelimizi kolayca test edebilir ve dil işleme yeteneklerini doğrudan görebilirsiniz.
-   
-   ```python
-   from transformers import AutoTokenizer, AutoModelForCausalLM
-
-   def load_model(model_name):
-       tokenizer = AutoTokenizer.from_pretrained(model_name)
-       model = AutoModelForCausalLM.from_pretrained(model_name)
-       if tokenizer.eos_token_id is not None:
-           model.config.pad_token_id = tokenizer.eos_token_id
-       return model, tokenizer
-
-   def generate_response(model, tokenizer, input_text):
-       inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True, max_length=512)
-       outputs = model.generate(**inputs, max_length=512, num_return_sequences=1)
-       response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-       return response
-
-   def main():
-       model_name = "aerdincdal/CBDDO-LLM-8B-Instruct-v1" 
-       model, tokenizer = load_model(model_name)
-       user_input = "Mona Lisa tablosunun önemini açıkla."
-       response = generate_response(model, tokenizer, user_input)
-       print("Response:", response)
-
-   if __name__ == "__main__":
-       main()
-   ```
-
-3. **Başlayın!**
-   Artık modelimizle metin oluşturabilir, çeviri yapabilir, sorularınıza yanıt bulabilir, metinleri özetleyebilir ve hatta Python kodları yazabilirsiniz. Örneğin, bir metni büyük harfe çeviren Python fonksiyonu yazabilirsiniz:
-
-   ```python
-   def metni_buyuk_harfe_cevir(metin):
-       """Bir metni büyük harflere çevirir."""
-       return metin.upper()
-
-   metin = "Bu bir deneme metnidir."
-   print(metni_buyuk_harfe_cevir(metin))
-   ```
-
-Bu basit adımlarla, Türkçe doğal dil işleme yeteneklerinin sınırlarını zorlayabilir ve dil modelimizin size nasıl yardımcı olabileceğini keşfedebilirsiniz. Bizimle bu teknoloji yolculuğuna çıkın ve dil işleme kapasitenizi genişletin!
+---
+license: mit
+---

config.json

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+{
+  "_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "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,
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.1",
+  "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": "4.40.1"
+}

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