From 95a36037599b63b5fafc2ce40bddf3bdad3b3962 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 9 Jun 2026 07:06:12 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: mesolitica/malaysian-llama2-7b-32k-instructions Source: Original Platform --- .gitattributes | 52 ++ README.md | 113 +++++ chat-7b-vs-chat-malaysian-llama2-7b.ipynb | 587 ++++++++++++++++++++++ config.json | 26 + configuration.json | 1 + generation_config.json | 10 + model-00001-of-00002.safetensors | 3 + model-00002-of-00002.safetensors | 3 + model.safetensors.index.json | 298 +++++++++++ special_tokens_map.json | 23 + tokenizer.json | 3 + tokenizer.model | 3 + tokenizer_config.json | 34 ++ 13 files changed, 1156 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 chat-7b-vs-chat-malaysian-llama2-7b.ipynb create mode 100644 config.json create mode 100644 configuration.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00002.safetensors create mode 100644 model-00002-of-00002.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer.model create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..71ea05c --- /dev/null +++ b/.gitattributes @@ -0,0 +1,52 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bin.* filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs 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0000000..2902582 --- /dev/null +++ b/README.md @@ -0,0 +1,113 @@ +--- +language: +- ms +--- + +# QLORA Malaysian Llama2 7B 32k chat completions + +QLORA https://huggingface.co/mesolitica/llama-7b-hf-32768-fpf on translated UltraChat, https://huggingface.co/datasets/mesolitica/google-translate-ultrachat. + +We use exact Llama2 chat template. + +README at https://github.com/mesolitica/malaya/tree/5.1/session/llama2#7b-16384-context-length-flash-attention-2 + +## how-to + +```python +from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig +import torch + +def parse_llama_chat(messages): + + system = messages[0]['content'] + user_query = messages[-1]['content'] + + users, assistants = [], [] + for q in messages[1:-1]: + if q['role'] == 'user': + users.append(q['content']) + elif q['role'] == 'assistant': + assistants.append(q['content']) + + texts = [f'[INST] <>\n{system}\n<>\n\n'] + for u, a in zip(users, assistants): + texts.append(f'{u.strip()} [/INST] {a.strip()} [INST] ') + texts.append(f'{user_query.strip()} [/INST]') + prompt = ''.join(texts).strip() + return prompt + +TORCH_DTYPE = 'bfloat16' +nf4_config = BitsAndBytesConfig( + load_in_4bit=True, + bnb_4bit_quant_type='nf4', + bnb_4bit_use_double_quant=True, + bnb_4bit_compute_dtype=getattr(torch, TORCH_DTYPE) +) + +tokenizer = AutoTokenizer.from_pretrained('mesolitica/malaysian-llama2-7b-32k-instructions') +model = AutoModelForCausalLM.from_pretrained( + 'mesolitica/malaysian-llama2-7b-32k-instructions', + use_flash_attention_2 = True, + quantization_config = nf4_config +) + +messages = [ + {'role': 'system', 'content': 'awak adalah AI yang mampu jawab segala soalan'}, + {'role': 'user', 'content': 'kwsp tu apa'} +] +prompt = parse_llama_chat(messages) +inputs = tokenizer([prompt], return_tensors='pt', add_special_tokens=False).to('cuda') +generate_kwargs = dict( + inputs, + max_new_tokens=1024, + top_p=0.95, + top_k=50, + temperature=0.9, + do_sample=True, + num_beams=1, +) +r = model.generate(**generate_kwargs) +print(tokenizer.decode(r[0])) +``` + +```text +' [INST] <> +awak adalah AI yang mampu jawab segala soalan +<> + +kwsp tu apa [/INST] Kumpulan Wang Simpanan Pekerja (KWSP) ialah sebuah badan berkanun yang ditubuhkan di Malaysia yang menguruskan tabung simpanan tetap pekerja bagi tujuan persaraan dan perancangan masa depan. Diasaskan pada tahun 1951, KWSP bertanggungjawab untuk mengumpul dan menguruskan sumber daripada majikan dan pekerja, dan juga menyediakan pelbagai faedah kepada ahli seperti dividen dan akses kepada pengeluaran simpanan pada usia persaraan. KWSP juga memainkan peranan penting dalam menyediakan perlindungan sosial dan pembangunan ekonomi di Malaysia, dengan mempromosikan simpanan pengguna dan meningkatkan kadar celik kewangan dalam kalangan rakyat. ' +``` + +```python +messages = [ + {'role': 'system', 'content': 'awak adalah AI yang mampu jawab segala soalan'}, + {'role': 'user', 'content': 'awat malaysia ada jabatan koko, malaysia bukan buat keluaq koko banyak pun'} +] +prompt = parse_llama_chat(messages) +inputs = tokenizer([prompt], return_tensors='pt', add_special_tokens=False).to('cuda') +generate_kwargs = dict( + inputs, + max_new_tokens=1024, + top_p=0.95, + top_k=50, + temperature=0.9, + do_sample=True, + num_beams=1, +) +r = model.generate(**generate_kwargs) +print(tokenizer.decode(r[0])) +``` + +```text + [INST] <> +awak adalah AI yang mampu jawab segala soalan +<> + +awat malaysia ada jabatan koko, malaysia bukan buat keluaq koko banyak pun [/INST] Penanaman koko di Malaysia bermula pada tahun 1950-an, dengan pengeluaran koko kering pertama dihasilkan pada tahun 1958. Pada masa itu, negara ini menjadi pembekal koko terbesar di dunia, dan industri ini terus berkembang dan mewujudkan ribuan pekerjaan dalam pemprosesan dan pengeluaran koko. + +Walau bagaimanapun, penurunan harga koko di pasaran antarabangsa pada tahun 1980-an menyebabkan pengeluaran koko Malaysia menurun, dan negara ini telah mengubah tumpuan daripada penanaman koko kepada komoditi lain seperti minyak kelapa sawit dan getah. + +Walaupun Malaysia bukan pengeluar koko yang besar, industri koko tempatan masih penting dari segi ekonomi dan sosial. Koko ialah komoditi yang diperdagangkan di bursa tempatan, dan pengeluar koko tempatan menghasilkan koko kering yang dieksport ke seluruh dunia. + +Jabatan Koko Malaysia ialah sebuah agensi kerajaan yang bertanggungjawab untuk membangunkan industri koko dan mempromosikan pengeluaran koko. Agensi ini bekerjasama dengan industri untuk meningkatkan produktiviti dan memastikan kualiti produk koko Malaysia. Ia juga menggalakkan usaha pembangunan pekebun kecil untuk mempromosikan industri koko dan mewujudkan peluang pekerjaan dan ekonomi di kawasan pedalaman. +``` \ No newline at end of file diff --git a/chat-7b-vs-chat-malaysian-llama2-7b.ipynb b/chat-7b-vs-chat-malaysian-llama2-7b.ipynb new file mode 100644 index 0000000..311cca8 --- /dev/null +++ b/chat-7b-vs-chat-malaysian-llama2-7b.ipynb @@ -0,0 +1,587 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "66b70728", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Loading the tokenizer from the `special_tokens_map.json` and the `added_tokens.json` will be removed in `transformers 5`, it is kept for forward compatibility, but it is recommended to update your `tokenizer_config.json` by uploading it again. You will see the new `added_tokens_decoder` attribute that will store the relevant information.\n" + ] + } + ], + "source": [ + "from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig\n", + "import torch\n", + "\n", + "tokenizer = AutoTokenizer.from_pretrained('meta-llama/Llama-2-13b-hf')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d608fb34", + "metadata": {}, + "outputs": [], + "source": [ + "nf4_config = BitsAndBytesConfig(\n", + " load_in_4bit=True,\n", + " bnb_4bit_quant_type='nf4',\n", + " bnb_4bit_use_double_quant=True,\n", + " bnb_4bit_compute_dtype=torch.bfloat16\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "4d63a1ec", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "81183d23312f44c395ebc24c90b00b9a", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading (…)lve/main/config.json: 0%| | 0.00/614 [00:00[INST] <>\\n{system}\\n<>\\n\\n']\n", + " for u, a in zip(users, assistants):\n", + " texts.append(f'{u.strip()} [/INST] {a.strip()} [INST] ')\n", + " texts.append(f'{user_query.strip()} [/INST]')\n", + " prompt = ''.join(texts).strip()\n", + " return prompt" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "af485f12", + "metadata": {}, + "outputs": [], + "source": [ + "import time\n", + "from tqdm import tqdm\n", + "\n", + "kwargs = {\n", + " 'temperature': 0.9, \n", + " 'max_new_tokens': 256, \n", + " 'top_p': 0.95, \n", + " 'repetition_penalty': 1.0, \n", + " 'do_sample': True,\n", + " 'num_beams': 1,\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "bde9c04f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'[INST] <>\\nAnda adalah pembantu AI yang berguna dan mampu jawab segala soalan yang diberikan. Jawapan yang diberikan haruslah panjang dan tepat.\\n<>\\n\\nkwsp tu apa [/INST]'" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "messages = [\n", + " {'role': 'system', 'content': 'Anda adalah pembantu AI yang berguna dan mampu jawab segala soalan yang diberikan. Jawapan yang diberikan haruslah panjang dan tepat.'},\n", + " {'role': 'user', 'content': 'kwsp tu apa'}\n", + "]\n", + "prompt = parse_llama_chat(messages)\n", + "prompt" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "8209faad", + "metadata": {}, + "outputs": [], + "source": [ + "inputs = tokenizer([prompt], return_tensors='pt').to('cuda')\n", + "generate_kwargs = dict(inputs)\n", + "generate_kwargs = {**generate_kwargs, **kwargs}" + ] + }, + { + "cell_type": "markdown", + "id": "3330733b", + "metadata": {}, + "source": [ + "## Chat 7B" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "09407603", + "metadata": {}, + "outputs": [], + "source": [ + "o = base_model.generate(**generate_kwargs)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "c76fc2b7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "As an AI language model, I can assist with a wide range of questions and tasks. Here are some examples of what I can help with:\n", + "1. Answering questions: I can provide detailed and accurate answers to various questions on a variety of topics, including science, history, technology, and more.\n", + "2. Generating text: I can produce text on a given topic or subject, including articles, stories, and other types of writing.\n", + "3. Translation: I can translate text from one language to another, including popular languages such as Spanish, French, German, Chinese, and many more.\n", + "4. Summarization: I can summarize long pieces of text, such as articles or documents, into shorter, more digestible versions.\n", + "5. Creative writing: I can generate creative content, such as poetry or short stories, based on prompts or topics provided.\n", + "6. Conversation: I can engage in natural-sounding conversations, using context and understanding to respond to questions and statements.\n", + "7. Language understanding: I can understand and interpret natural language, including idioms, sarcasm, and other forms of nuanced communication.\n", + "8. Dialogue generation: I can generate\n" + ] + } + ], + "source": [ + "print(tokenizer.decode(o[0], skip_special_tokens = True).split('[/INST]')[-1].strip())" + ] + }, + { + "cell_type": "markdown", + "id": "f48183e9", + "metadata": {}, + "source": [ + "## Malaysian Llama2 7B 32k" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "0379d919", + "metadata": {}, + "outputs": [], + "source": [ + "o = fpf_model.generate(**generate_kwargs)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "c528ac10", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Kumpulan Wang Simpanan Pekerja (KWSP) ialah organisasi yang ditubuhkan di Malaysia untuk membantu rakyatnya menyimpan wang untuk persaraan. KWSP menawarkan beberapa pelan untuk memenuhi keperluan penyimpan berbeza, dengan pelaburan dalam dana, ekuiti, instrumen bon dan lain-lain. Keuntungan dan dividen daripada pelaburan tersebut digunakan untuk melindungi kepentingan simpanan persaraan penyimpan. KWSP juga menyediakan akses mudah kepada penyimpan untuk menyemak penyata dan akaun, serta untuk memindahkan dana ke pelaburan baharu atau membuat pengeluaran simpanan persaraan. Ini membolehkan penyimpan memperoleh pulangan yang dijangka di atas inflasi dan\n" + ] + } + ], + "source": [ + "print(tokenizer.decode(o[0], skip_special_tokens = True).split('[/INST]')[-1].strip())" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "a5ab5e88", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'[INST] <>\\nAnda adalah pembantu AI yang berguna dan mampu jawab segala soalan yang diberikan. Jawapan yang diberikan haruslah panjang dan tepat.\\n<>\\n\\nawat malaysia ada lembaga koko, malaysia bukan buat keluaq koko banyak pun [/INST]'" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "messages = [\n", + " {'role': 'system', 'content': 'Anda adalah pembantu AI yang berguna dan mampu jawab segala soalan yang diberikan. Jawapan yang diberikan haruslah panjang dan tepat.'},\n", + " {'role': 'user', 'content': 'awat malaysia ada lembaga koko, malaysia bukan buat keluaq koko banyak pun'}\n", + "]\n", + "prompt = parse_llama_chat(messages)\n", + "prompt" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "33bcbd70", + "metadata": {}, + "outputs": [], + "source": [ + "inputs = tokenizer([prompt], return_tensors='pt').to('cuda')\n", + "generate_kwargs = dict(inputs)\n", + "generate_kwargs = {**generate_kwargs, **kwargs}" + ] + }, + { + "cell_type": "markdown", + "id": "20594ee7", + "metadata": {}, + "source": [ + "## Chat 7B" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "73773791", + "metadata": {}, + "outputs": [], + "source": [ + "o = base_model.generate(**generate_kwargs)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "8b173ddb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "I apologize, but the statement \"Malaysia ada lembaga koko\" is not accurate. Malaysia does not have a chocolate industry. While Malaysia is known for its rich cultural heritage and diverse food scene, chocolate is not a significant part of the country's culinary traditions.\n", + "However, there are some chocolate brands in Malaysia that produce high-quality chocolate products, such as dark chocolate, milk chocolate, and white chocolate. These brands often source their cocoa beans from sustainable farms in West Africa, South America, and other parts of Southeast Asia.\n", + "Some popular chocolate brands in Malaysia include:\n", + "1. Cacao & Co.: This brand offers a range of premium chocolate products, including dark chocolate bars, truffles, and gift boxes.\n", + "2. The Chocolate Room: This boutique chocolate shop in Kuala Lumpur offers a wide range of artisanal chocolate products, including handcrafted truffles, chocolate bars, and gift boxes.\n", + "3. Chocolate Dreams: This\n" + ] + } + ], + "source": [ + "print(tokenizer.decode(o[0], skip_special_tokens = True).split('[/INST]')[-1].strip())" + ] + }, + { + "cell_type": "markdown", + "id": "4e43759c", + "metadata": {}, + "source": [ + "## Malaysian Llama2 7B 32k" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "5a0a6dbf", + "metadata": {}, + "outputs": [], + "source": [ + "o = fpf_model.generate(**generate_kwargs)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "a67751d8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Lembaga Koko Malaysia ialah agensi kerajaan yang ditubuhkan untuk mengawal selia industri koko Malaysia. Lembaga Koko ditubuhkan pada tahun 1988 sebagai sebahagian daripada usaha untuk meningkatkan lagi industri koko Malaysia. Tujuan utama lembaga adalah untuk mempromosikan dan membangunkan industri koko Malaysia, termasuk menggalakkan penanaman dan pengeluaran koko, meningkatkan perdagangan koko dan produk koko dan menyediakan sokongan teknikal dan latihan untuk industri koko.\n", + "\n", + "Walaupun Malaysia tidak menanam banyak koko, ia masih merupakan salah satu negara pengeluar koko utama di dunia, dan pengeksport utama koko di rantau Asia. Koko menyumbang kira-kira 2.8% daripada jum\n" + ] + } + ], + "source": [ + "print(tokenizer.decode(o[0], skip_special_tokens = True).split('[/INST]')[-1].strip())" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/config.json b/config.json new file mode 100644 index 0000000..5c7bb49 --- /dev/null +++ b/config.json @@ -0,0 +1,26 @@ +{ + "_name_or_path": "./7b-16k", + "architectures": [ + "LlamaForCausalLM" + ], + "bos_token_id": 1, + "eos_token_id": 2, + "hidden_act": "silu", + "hidden_size": 4096, + "initializer_range": 0.02, + "intermediate_size": 11008, + "max_position_embeddings": 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