Create README.md

README.md

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+# Model Card for peft with cenkersisman/TurkishWikipedia-LLM-7b-base
+
+**Library name:** peft
+
+**Base model:** mistralai/Mistral-7B-v0.1
+
+**Model Description:**
+
+This model was fine-tuned on Turkish Wikipedia texts using the peft library with Lora configuration.
+
+**Developed by:** [More Information Needed]
+
+**Funded by:** [Optional]: [More Information Needed]
+
+**Shared by:** [Optional]: [More Information Needed]
+
+**Model type:** Fine-tuned language model
+
+**Language(s) (NLP):** Turkish
+
+**License:** [More Information Needed]
+
+**Finetuned from model:** mistralai/Mistral-7B-v0.1
+
+**Model Sources:**
+
+- **Repository:** [More Information Needed]
+- **Paper:** [Optional]: [More Information Needed]
+- **Demo:** [Optional]: [To be implemented]
+
+## Uses
+
+**Direct Use**
+
+This model can be used for various NLP tasks, including:
+
+- Text generation
+- Machine translation
+- Question answering
+- Text summarization
+
+**Downstream Use**
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+- **Bias:** The model may inherit biases from the training data, which is Wikipedia text. Biases could include cultural biases or biases in how information is presented on Wikipedia.
+- **Risks:** The model may generate text that is offensive, misleading, or factually incorrect. It is important to be aware of these risks and to use the model responsibly.
+- **Limitations:** The model may not perform well on all tasks, and it may not be able to generate text that is creative or original.
+
+## Recommendations
+
+- Users (both direct and downstream) should be aware of the risks, biases and limitations of the model.
+- It is important to evaluate the outputs of the model carefully before using them in any application.
+
+## How to Get Started with the Model
+
+The following code snippet demonstrates how to load the fine-tuned model and generate text:
+
+Python
+
+```
+from transformers import AutoModelForCausalLM, LlamaTokenizer, pipeline
+
+# Load the model and tokenizer
+folder = "cenkersisman/TurkishWikipedia-LLM-7b-base"
+device = "cuda"
+model = AutoModelForCausalLM.from_pretrained(folder).to(device)
+tokenizer = LlamaTokenizer.from_pretrained(folder)
+
+# Create a pipeline for text generation
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device_map=device, max_new_tokens=128, return_full_text=True, repetition_penalty=1.1)
+
+# Generate text
+def generate_output(user_query):
+    outputs = pipe(user_query, do_sample=True, temperature=0.1, top_k=10, top_p=0.9)
+    return outputs[0]["generated_text"]
+
+# Example usage
+user_query = "brezilya'nın nüfus olarak dünyanın en büyük"
+output = generate_output(user_query)
+print(output)
+```
+
+This code will load the fine-tuned model from the "cenkersisman/TurkishWikipedia-LLM-7b-base", create a pipeline for text generation, and then generate text based on the provided user query.
+
+## Training Details
+
+**Training Data**
+
+- 9 million sentences from Turkish Wikipedia.
+
+**Training Procedure**
+
+- **Preprocessing:** The data was preprocessed by tokenizing the text and adding special tokens.
+  
+- **Training Hyperparameters**
+  
+  - Training regime: Fine-tuning with Lora configuration
+  - Speeds, Sizes, Times: [More Information Needed]
+
+**Evaluation**
+
+- Testing Data, Factors & Metrics: [More Information Needed]
+  
+- **Results:** [More Information Needed]
+  
+
+## Summary
+
+- This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 trained on Turkish Wikipedia text.
+- The model can be used for various NLP tasks, including text generation.
+- It is important to be aware of the risks, biases, and limitations of the model before using it.
+
+## Environmental Impact
+
+- The environmental impact of training this model can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
+  
+- Hardware Type: [More Information Needed]
+  
+- Hours used: [More Information Needed]
+  
+- Cloud Provider: [More Information Needed]
+  
+- Compute Region: [More Information Needed]
+  
+- Carbon Emitted: [More Information Needed]
+  
+
+## Technical Specifications
+
+- **Model Architecture and Objective:**
+  - The model architecture is based on mistralai/Mistral-7B-v0.1.
+  - The objective of the fine-tuning process was to improve the model's