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README.md

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+
+---
+
+datasets:
+- cerebras/SlimPajama-627B
+- HuggingFaceH4/ultrachat_200k
+- bigcode/starcoderdata
+- HuggingFaceH4/ultrafeedback_binarized
+language:
+- en
+metrics:
+- accuracy
+- speed
+library_name: transformers
+tags:
+- coder
+- Text-Generation
+- Transformers
+- HelpingAI
+license: mit
+widget:
+- text: |
+    <|system|>
+    You are a chatbot who can code!</s>
+    <|user|>
+    Write me a function to search for OEvortex on youtube use Webbrowser .</s>
+    <|assistant|>
+- text: |
+    <|system|>
+    You are a chatbot who can be a teacher!</s>
+    <|user|>
+    Explain me working of AI .</s>
+    <|assistant|>
+model-index:
+- name: HelpingAI-Lite
+  results:
+  - task:
+      type: text-generation
+    metrics:
+    - name: Epoch
+      type: Training Epoch
+      value: 3
+    - name: Eval Logits/Chosen
+      type: Evaluation Logits for Chosen Samples
+      value: -2.707406759262085
+    - name: Eval Logits/Rejected
+      type: Evaluation Logits for Rejected Samples
+      value: -2.65652441978546
+    - name: Eval Logps/Chosen
+      type: Evaluation Log-probabilities for Chosen Samples
+      value: -370.129670421875
+    - name: Eval Logps/Rejected
+      type: Evaluation Log-probabilities for Rejected Samples
+      value: -296.073825390625
+    - name: Eval Loss
+      type: Evaluation Loss
+      value: 0.513750433921814
+    - name: Eval Rewards/Accuracies
+      type: Evaluation Rewards and Accuracies
+      value: 0.738095223903656
+    - name: Eval Rewards/Chosen
+      type: Evaluation Rewards for Chosen Samples
+      value: -0.0274422804903984
+    - name: Eval Rewards/Margins
+      type: Evaluation Rewards Margins
+      value: 1.008722543614307
+    - name: Eval Rewards/Rejected
+      type: Evaluation Rewards for Rejected Samples
+      value: -1.03616464138031
+    - name: Eval Runtime
+      type: Evaluation Runtime
+      value: 93.5908
+    - name: Eval Samples
+      type: Number of Evaluation Samples
+      value: 2000
+    - name: Eval Samples per Second
+      type: Evaluation Samples per Second
+      value: 21.37
+    - name: Eval Steps per Second
+      type: Evaluation Steps per Second
+      value: 0.673
+
+---
+
+![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)
+
+# QuantFactory/HelpingAI-Lite-GGUF
+This is quantized version of [OEvortex/HelpingAI-Lite](https://huggingface.co/OEvortex/HelpingAI-Lite) created using llama.cpp
+
+# Original Model Card
+
+
+# HelpingAI-Lite
+# Subscribe to my YouTube channel
+[Subscribe](https://youtube.com/@OEvortex)
+
+GGUF version [here](https://huggingface.co/OEvortex/HelpingAI-Lite-GGUF)
+
+HelpingAI-Lite is a lite version of the HelpingAI model that can assist with coding tasks. It's trained on a diverse range of datasets and fine-tuned to provide accurate and helpful responses.
+
+## License
+
+This model is licensed under MIT.
+
+## Datasets
+
+The model was trained on the following datasets:
+- cerebras/SlimPajama-627B
+- bigcode/starcoderdata
+- HuggingFaceH4/ultrachat_200k
+- HuggingFaceH4/ultrafeedback_binarized
+
+## Language
+
+The model supports English language.
+
+## Usage
+
+# CPU and GPU code
+
+```python
+from transformers import pipeline
+from accelerate import Accelerator
+
+# Initialize the accelerator
+accelerator = Accelerator()
+
+# Initialize the pipeline
+pipe = pipeline("text-generation", model="OEvortex/HelpingAI-Lite", device=accelerator.device)
+
+# Define the messages
+messages = [
+    {
+        "role": "system",
+        "content": "You are a chatbot who can help code!",
+    },
+    {
+        "role": "user",
+        "content": "Write me a function to calculate the first 10 digits of the fibonacci sequence in Python and print it out to the CLI.",
+    },
+]
+
+# Prepare the prompt
+prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+# Generate predictions
+outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+
+# Print the generated text
+print(outputs[0]["generated_text"])
+```