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Model: hon9kon9ize/CantoneseLLMChat-v1.0-7B
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+library_name: transformers
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+base_model: hon9kon9ize/CantoneseLLM-v1.0
+model-index:
+- name: CantoneseLLMChat-v1.0-7B
+  results: []
+---
+
+
+
+# CantoneseLLMChat-v1.0-7B
+
+![front_image](cantonese_llm_v1.jpg)
+
+
+Cantonese LLM Chat v1.0 is the first generation Cantonese LLM from hon9kon9ize.
+Building upon the sucess of [v0.5 preview](https://huggingface.co/hon9kon9ize/CantoneseLLMChat-v0.5), the model excels in Hong Kong related specific knowledge and Cantonese conversation.
+
+## Model description
+Base model obtained via Continuous Pre-Training of [Qwen 2.5 7B](https://huggingface.co/Qwen/Qwen2.5-7B) with 600 millions publicaly available Hong Kong news articles and Cantonese websites. 
+Instructions fine-tuned model trained with a dataset consists of 75,000 instrutions pairs. 45,000 pairs were Cantonese insturctions generated by other LLMs and reviewed by humans. 
+
+The model trained with 1 Nvidia H100 80GB HBM3 GPU on [Genkai Supercomputer](https://www.cc.kyushu-u.ac.jp/scp/eng/system/Genkai/hardware/).
+
+## Basic Usage
+```
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = "hon9kon9ize/CantoneseLLMChat-v1.0-7B"
+
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16, 
+    device_map="auto", 
+)
+
+def chat(messages, temperature=0.9, max_new_tokens=200):
+    input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt').to('cuda:0')
+    output_ids = model.generate(input_ids, max_new_tokens=max_new_tokens, temperature=temperature)
+    response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=False)
+    return response
+
+prompt = "邊個係香港特首？"
+
+messages = [
+    {"role": "system", "content": "you are a helpful assistant."},
+    {"role": "user", "content": prompt}
+]
+
+print(chat(messages)) # 香港特別行政區行政長官係李家超。<|im_end|>
+```
+
+## Performance
+Best in class open source LLM in understanding Cantonese and Hong Kong culture in the [HK-Eval Benchmark](https://arxiv.org/pdf/2503.12440). 
+However, as one could observe, reasoning models have performed dramatically better than their counterparts. We are currently working on reasoning models for v2.
+
+| Model                     | HK Culture (zero-shot) | Cantonese Linguistics |
+|---------------------------|:----------------------:|:---------------------:|
+| CantonesellmChat v0.5 6B  |          52.0%         |         12.8%         |
+| CantonesellmChat v0.5 34B |          72.5%         |         54.5%         |
+| CantonesellmChat v1.0 3B  |          56.0%         |         45.7%         |
+| CantonesellmChat v1.0 7B  |          60.3%         |         46.5%         |
+| CantonesellmChat v1.0 32B |          69.8%         |         52.7%         |
+| CantonesellmChat v1.0 72B |          75.4%         |         59.6%         |
+| Llama 3.1 8B Instruct     |          45.6%         |         35.1%         |
+| Llama 3.1 70B Instruct    |          63.0%         |         50.3%         |
+| Qwen2.5 7B Instruct       |          51.2%         |         30.3%         |
+| Qwen2.5 32B Instruct      |          59.9%         |         45.1%         |
+| Qwen2.5 72B Instruct      |          65.9%         |         45.9%         |
+| Claude 3.5 Sonnet         |          71.7%         |         63.2%         |
+| DeepSeek R1               |          88.8%         |         77.5%         |
+| Gemini 2.0 Flash          |          80.2%         |         75.3%         |
+| Gemini 2.5 Pro            |          92.1%         |         87.3%         |
+| GPT4o                     |          77.5%         |         63.8%         |
+| GPT4o-mini                |          55.6%         |         57.3%         |

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all_results.json

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+    "train_loss": 0.937529916860168,
+    "train_runtime": 37609.4943,
+    "train_samples_per_second": 5.32,
+    "train_steps_per_second": 0.166
+}

config.json

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+  "_name_or_path": "hon9kon9ize/Qwen2.5-7B-cpt",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
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+  "max_position_embeddings": 131072,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
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+  "num_hidden_layers": 28,
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+  "use_cache": false,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

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+    "eval_runtime": 178.4011,
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+}

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+  "transformers_version": "4.45.0"
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