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Model: OEvortex/HelpingAI-Lite-1.5T
Source: Original Platform

.gitattributes

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README.md

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+---
+datasets:
+- cerebras/SlimPajama-627B
+- HuggingFaceH4/ultrachat_200k
+- bigcode/starcoderdata
+- HuggingFaceH4/ultrafeedback_binarized
+- OEvortex/vortex-mini
+- Open-Orca/OpenOrca
+language:
+- en
+metrics:
+- speed
+library_name: transformers
+tags:
+- Text-Generation
+- Transformers
+- HelpingAI
+license: other
+license_name: hsul
+license_link: https://huggingface.co/OEvortex/vortex-3b/raw/main/LICENSE.md
+widget:
+- text: |
+    <|system|>
+    You are a chatbot who can be a teacher!</s>
+    <|user|>
+    Explain me working of AI .</s>
+    <|assistant|>
+---
+🌟 **HelpingAI-Lite-1.5T Model Card** 🌟
+
+📊 **Datasets used:**
+- cerebras/SlimPajama-627B
+- HuggingFaceH4/ultrachat_200k
+- bigcode/starcoderdata
+- HuggingFaceH4/ultrafeedback_binarized
+- OEvortex/vortex-mini
+- Open-Orca/OpenOrca
+
+🗣️ **Language:**
+- English (en)
+
+
+🔒 **License:**
+
+
+HelpingAI Simplified Universal License (HSUL)
+
+
+🧠 **Model Overview:**
+HelpingAI-Lite-1.5T is an advanced version of the HelpingAI-Lite model, trained on a vast corpus of 1.5 trillion tokens. This extensive training data enables the model to provide precise and insightful responses, particularly for coding tasks.
+
+🔧 **Usage Example:**
+```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-1.5T", device=accelerator.device)
+
+# Define the messages
+messages = [
+    {
+        "role": "system",
+        "content": "You are a chatbot who can be a teacher",
+    },
+    {
+        "role": "user",
+        "content": "Explain me working of AI.",
+    },
+]
+
+# 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"])
+```

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 22,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.31.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 0,
+  "max_length": 2048,
+  "transformers_version": "4.31.0.dev0"
+}

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special_tokens_map.json

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tokenizer_config.json

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+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
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+  }
+}