commit bf58aa5936f237b694c9cf346804c2cd6357518a
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Mon Jun 1 05:40:17 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: IAmSkyDra/GemSUra-edu
    Source: Original Platform

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
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+unsloth.F16.gguf filter=lfs diff=lfs merge=lfs -text
+unsloth.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+unsloth.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitignore b/.gitignore
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+config.json
\ No newline at end of file
diff --git a/README.md b/README.md
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+---
+license: apache-2.0
+datasets:
+- IAmSkyDra/HCMUT_FAQ
+language:
+- vi
+tags:
+- education
+- text-generation-inference
+- gemma
+- llama-factory
+- unsloth
+widget:
+- text: Chào bạn
+  output:
+    text: >-
+      Chào bạn! Tôi là GemSUra-edu, một trợ lý AI được phát triển bởi Long
+      Nguyen.
+  example_title: Query 1
+
+- text: Hiệu trưởng hiện tại của trường Đại học Bách Khoa
+  output:
+    text: >-
+      Hiệu trưởng hiện tại của trường Đại học Bách Khoa là PGS. TS. Mai Thanh Phong.
+  example_title: Query 2
+
+- text: OISP là viết tắt của
+  output:
+    text: >-
+      Văn phòng Đào tạo Quốc tế (Office for International Study Programs)
+  example_title: Query 3
+---
+## Introduction
+
+GemSUra-edu is a large language model fine-tuned on a dataset of FAQs from HCMUT, based on the pre-trained model [GemSUra 2B](https://huggingface.co/ura-hcmut/GemSUra-2B) developed by the URA research group at Ho Chi Minh City University of Technology (HCMUT).
+
+## Inference (with Unsloth for higher speed)
+
+```python
+from unsloth import FastLanguageModel
+import torch
+
+# Load model and tokenizer
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name="IAmSkyDra/GemSUra-edu",
+    max_seq_length=4096,
+    dtype=None,
+    load_in_4bit=True
+)
+
+FastLanguageModel.for_inference(model)
+
+query_template = "<start_of_turn>user\n{query}<end_of_turn>\n<start_of_turn>model\n"
+
+while True:
+    query = input("Query: ")
+    if query.lower() == "exit":
+        break
+
+    query = query_template.format(query=query)
+    inputs = tokenizer(query, return_tensors="pt")
+
+    outputs = model.generate(**inputs, max_new_tokens=4096, use_cache=True)
+    generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    answer = generated_text[0].split("model\n")[1].strip()
+    print(answer)
+```
+
+## Inference (with Transformers)
+
+```python
+import transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+pipeline_kwargs = {
+    "temperature": 0.1,
+    "max_new_tokens": 4096,
+    "do_sample": True
+}
+
+if __name__ == "__main__":
+    # Load model
+    model = AutoModelForCausalLM.from_pretrained(
+        "IAmSkyDra/GemSUra-edu",
+        device_map="auto"
+    )
+    model.eval()
+
+    # Load tokenizer
+    tokenizer = AutoTokenizer.from_pretrained(
+        "IAmSkyDra/GemSUra-edu",
+        trust_remote_code=True
+    )
+
+    pipeline = transformers.pipeline(
+        model=model,
+        tokenizer=tokenizer,
+        return_full_text=False,
+        task='text-generation',
+        **pipeline_kwargs
+    )
+
+    query_template = "<start_of_turn>user\n{query}<end_of_turn>\n<start_of_turn>model\n"
+
+    while True:
+        query = input("Query: ")
+        if query.lower() == "exit":
+            break
+
+        query = query_template.format(query=query)
+        answer = pipeline(query)[0]["generated_text"]
+        answer = answer.split("model\n")[1].strip()
+        print(answer)
+```
+
+## Notation
+
+If you want to quantize the model for deployment on local devices, it should be quantized to at least 8 bits.
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diff --git a/config.json b/config.json
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+{
+  "_name_or_path": "ura-hcmut/GemSUra-2B",
+  "architectures": [
+    "GemmaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 2,
+  "eos_token_id": 1,
+  "head_dim": 256,
+  "hidden_act": "gelu",
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 16384,
+  "max_position_embeddings": 8192,
+  "model_type": "gemma",
+  "num_attention_heads": 8,
+  "num_hidden_layers": 18,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.42.4",
+  "use_cache": true,
+  "vocab_size": 256000
+}
diff --git a/generation_config.json b/generation_config.json
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+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.42.4"
+}
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