From 381216f9852f3f6fda69ce46a5bab7654f967ad6 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 6 Sep 2026 03:02:13 +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: scb10x/llama3.2-typhoon2-1b-instruct Source: Original Platform --- .gitattributes | 49 + README.md | 315 ++++++ config.json | 1 + configuration.json | 1 + generation_config.json | 17 + model.safetensors | 3 + special_tokens_map.json | 23 + tokenizer.json | 3 + tokenizer_config.json | 2063 +++++++++++++++++++++++++++++++++++++++ 9 files changed, 2475 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 configuration.json create mode 100644 generation_config.json create mode 100644 model.safetensors create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..21b3632 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,49 @@ +*.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 diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zstandard filter=lfs diff=lfs merge=lfs -text +*.tfevents* filter=lfs diff=lfs merge=lfs -text +*.db* filter=lfs diff=lfs merge=lfs -text +*.ark* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.gguf* filter=lfs diff=lfs merge=lfs -text +*.ggml filter=lfs diff=lfs merge=lfs -text +*.llamafile* filter=lfs diff=lfs merge=lfs -text +*.pt2 filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text + +tokenizer.json filter=lfs diff=lfs merge=lfs -text \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..858dd18 --- /dev/null +++ b/README.md @@ -0,0 +1,315 @@ +--- +license: llama3.2 +pipeline_tag: text-generation +--- + +**Llama3.2-Typhoon2-1B**: Thai Large Language Model (Instruct) + +**Llama3.2-Typhoon2-1B-instruct** is a instruct Thai 🇹🇭 large language model with 1 billion parameters, and it is based on Llama3.2-1B. + +For technical-report. please see our [arxiv](https://arxiv.org/abs/2412.13702). +*To acknowledge Meta's effort in creating the foundation model and to comply with the license, we explicitly include "llama-3.2" in the model name. + + +## **Performance** + +**Instruction-Following & Function Call Performance** + +
+ Typhoon General Performance +
+ +**Detail Performance** + +| Model | IFEval - TH | IFEval - EN | MT-Bench TH | MT-Bench EN | Thai Code-Switching (t=0.7) | Thai Code-Switching (t=1.0) | FunctionCall-TH | FunctionCall-EN | +|----------------------------|-------------|-------------|-------------|-------------|-----------------------------|-----------------------------|----------------|----------------| +| **Typhoon2 1b instruct** | **52.46%** | **53.35%** | **3.9725** | 5.2125 | 96.4% | **88%** | **34.96%** | **45.60%** | +| **Qwen2.5 1.5b instruct** | 44.42% | 48.45% | 2.9395 | **6.9343** | 82.6% | 20.6% | 13.83% | 17.88% | +| **llama3.2 1b instruct** | 31.76% | 51.15% | 2.5824 | 6.229 | **97.8%** | 22.6% | 29.88% | 36.50% | + + +## **Model Description** + +- **Model type**: A 1B instruct decoder-only model based on Llama architecture. +- **Requirement**: transformers 4.45.0 or newer. +- **Primary Language(s)**: Thai 🇹🇭 and English 🇬🇧 +- **License**: [Llama 3.2 Community License](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/LICENSE) + + +## Usage Example + +```python +from transformers import AutoTokenizer, AutoModelForCausalLM +import torch + +model_id = "scb10x/llama3.2-typhoon2-1b-instruct" + +tokenizer = AutoTokenizer.from_pretrained(model_id) +model = AutoModelForCausalLM.from_pretrained( + model_id, + torch_dtype=torch.bfloat16, + device_map="auto", +) + +messages = [ + {"role": "system", "content": "You are a male AI assistant named Typhoon created by SCB 10X to be helpful, harmless, and honest. Typhoon is happy to help with analysis, question answering, math, coding, creative writing, teaching, role-play, general discussion, and all sorts of other tasks. Typhoon responds directly to all human messages without unnecessary affirmations or filler phrases like “Certainly!”, “Of course!”, “Absolutely!”, “Great!”, “Sure!”, etc. Specifically, Typhoon avoids starting responses with the word “Certainly” in any way. Typhoon follows this information in all languages, and always responds to the user in the language they use or request. Typhoon is now being connected with a human. Write in fluid, conversational prose, Show genuine interest in understanding requests, Express appropriate emotions and empathy. Also showing information in term that is easy to understand and visualized."}, + {"role": "user", "content": "ขอสูตรไก่ย่าง"}, +] + +input_ids = tokenizer.apply_chat_template( + messages, + add_generation_prompt=True, + return_tensors="pt" +).to(model.device) + +terminators = [ + tokenizer.eos_token_id, + tokenizer.convert_tokens_to_ids("<|eot_id|>") +] +## Typhoon 1b need low temperature to inference. +outputs = model.generate( + input_ids, + max_new_tokens=512, + eos_token_id=terminators, + do_sample=True, + temperature=0.4, + top_p=0.9, +) +response = outputs[0][input_ids.shape[-1]:] +print(tokenizer.decode(response, skip_special_tokens=True)) +``` + + +## Function-Call Example +```python +import torch +from transformers import AutoModelForCausalLM, AutoTokenizer +import ast +model_name = "scb10x/llama3.2-typhoon2-1b-instruct" +tokenizer = AutoTokenizer.from_pretrained(model_name) +model = AutoModelForCausalLM.from_pretrained( + model_name, torch_dtype=torch.bfloat16, device_map="auto", +) + +get_weather_api = { + "name": "get_weather", + "description": "Get the current weather for a location", + "parameters": { + "type": "object", + "properties": { + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, New York", + }, + "unit": { + "type": "string", + "enum": ["celsius", "fahrenheit"], + "description": "The unit of temperature to return", + }, + }, + "required": ["location"], + }, +} + + +search_api = { + "name": "search", + "description": "Search for information on the internet", + "parameters": { + "type": "object", + "properties": { + "query": { + "type": "string", + "description": "The search query, e.g. 'latest news on AI'", + } + }, + "required": ["query"], + }, +} + +get_stock = { + "name": "get_stock_price", + "description": "Get the stock price", + "parameters": { + "type": "object", + "properties": { + "symbol": { + "type": "string", + "description": "The stock symbol, e.g. AAPL, GOOG", + } + }, + "required": ["symbol"], + }, +} +# Tool input are same format with OpenAI tools +openai_format_tools = [get_weather_api, search_api, get_stock] + +messages = [ + {"role": "system", "content": "You are an expert in composing functions."}, + {"role": "user", "content": "ขอราคาหุ้น Tasla (TLS) และ Amazon (AMZ) ?"}, +] + +inputs = tokenizer.apply_chat_template( + messages, tools=openai_format_tools, add_generation_prompt=True, return_tensors="pt" +).to(model.device) + +outputs = model.generate( + inputs, + max_new_tokens=512, + do_sample=True, + temperature=0.7, + num_return_sequences=1, + eos_token_id=[tokenizer.eos_token_id, 128009], +) +response = outputs[0][inputs.shape[-1]:] + +print("Here Output:", tokenizer.decode(response, skip_special_tokens=True)) + + +# Decoding function utility +def resolve_ast_by_type(value): + if isinstance(value, ast.Constant): + if value.value is Ellipsis: + output = "..." + else: + output = value.value + elif isinstance(value, ast.UnaryOp): + output = -value.operand.value + elif isinstance(value, ast.List): + output = [resolve_ast_by_type(v) for v in value.elts] + elif isinstance(value, ast.Dict): + output = { + resolve_ast_by_type(k): resolve_ast_by_type(v) + for k, v in zip(value.keys, value.values) + } + elif isinstance( + value, ast.NameConstant + ): # Added this condition to handle boolean values + output = value.value + elif isinstance( + value, ast.BinOp + ): # Added this condition to handle function calls as arguments + output = eval(ast.unparse(value)) + elif isinstance(value, ast.Name): + output = value.id + elif isinstance(value, ast.Call): + if len(value.keywords) == 0: + output = ast.unparse(value) + else: + output = resolve_ast_call(value) + elif isinstance(value, ast.Tuple): + output = tuple(resolve_ast_by_type(v) for v in value.elts) + elif isinstance(value, ast.Lambda): + output = eval(ast.unparse(value.body[0].value)) + elif isinstance(value, ast.Ellipsis): + output = "..." + elif isinstance(value, ast.Subscript): + try: + output = ast.unparse(value.body[0].value) + except: + output = ast.unparse(value.value) + "[" + ast.unparse(value.slice) + "]" + else: + raise Exception(f"Unsupported AST type: {type(value)}") + return output + + +def resolve_ast_call(elem): + func_parts = [] + func_part = elem.func + while isinstance(func_part, ast.Attribute): + func_parts.append(func_part.attr) + func_part = func_part.value + if isinstance(func_part, ast.Name): + func_parts.append(func_part.id) + func_name = ".".join(reversed(func_parts)) + args_dict = {} + for arg in elem.keywords: + output = resolve_ast_by_type(arg.value) + args_dict[arg.arg] = output + return {func_name: args_dict} + + +def ast_parse(input_str, language="Python"): + if language == "Python": + cleaned_input = input_str.strip("[]'") + parsed = ast.parse(cleaned_input, mode="eval") + extracted = [] + if isinstance(parsed.body, ast.Call): + extracted.append(resolve_ast_call(parsed.body)) + else: + for elem in parsed.body.elts: + assert isinstance(elem, ast.Call) + extracted.append(resolve_ast_call(elem)) + return extracted + else: + raise NotImplementedError(f"Unsupported language: {language}") + + +def parse_nested_value(value): + """ + Parse a potentially nested value from the AST output. + + Args: + value: The value to parse, which could be a nested dictionary, which includes another function call, or a simple value. + + Returns: + str: A string representation of the value, handling nested function calls and nested dictionary function arguments. + """ + if isinstance(value, dict): + # Check if the dictionary represents a function call (i.e., the value is another dictionary or complex structure) + if all(isinstance(v, dict) for v in value.values()): + func_name = list(value.keys())[0] + args = value[func_name] + args_str = ", ".join( + f"{k}={parse_nested_value(v)}" for k, v in args.items() + ) + return f"{func_name}({args_str})" + else: + # If it's a simple dictionary, treat it as key-value pairs + return ( + "{" + + ", ".join(f"'{k}': {parse_nested_value(v)}" for k, v in value.items()) + + "}" + ) + return repr(value) + +def default_decode_ast_prompting(result, language="Python"): + result = result.strip("`\n ") + if not result.startswith("["): + result = "[" + result + if not result.endswith("]"): + result = result + "]" + decoded_output = ast_parse(result, language) + return decoded_output + +fc_result = default_decode_ast_prompting(tokenizer.decode(response, skip_special_tokens=True)) +print(fc_result) # [{'Function': {'arguments': '{"symbol": "TLS"}', 'name': 'get_stock_price'}}, {'Function': {'arguments': '{"symbol": "AMZ"}', 'name': 'get_stock_price'}}] +``` + +## **Intended Uses & Limitations** + +This model is an instructional model. However, it’s still undergoing development. It incorporates some level of guardrails, but it still may produce answers that are inaccurate, biased, or otherwise objectionable in response to user prompts. We recommend that developers assess these risks in the context of their use case. + +## **Follow us** + +**https://twitter.com/opentyphoon** + +## **Support** + +**https://discord.gg/us5gAYmrxw** + + +## **Citation** + +- If you find Typhoon2 useful for your work, please cite it using: +``` +@misc{typhoon2, + title={Typhoon 2: A Family of Open Text and Multimodal Thai Large Language Models}, + author={Kunat Pipatanakul and Potsawee Manakul and Natapong Nitarach and Warit Sirichotedumrong and Surapon Nonesung and Teetouch Jaknamon and Parinthapat Pengpun and Pittawat Taveekitworachai and Adisai Na-Thalang and Sittipong Sripaisarnmongkol and Krisanapong Jirayoot and Kasima Tharnpipitchai}, + year={2024}, + eprint={2412.13702}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + url={https://arxiv.org/abs/2412.13702}, +} +``` \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..33ce0d0 --- /dev/null +++ b/config.json @@ -0,0 +1 @@ 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Based on the question, you will need to make one or more function/tool calls to achieve the purpose.\" }}\n {{- \"If none of the function can be used, point it out. If the given question lacks the parameters required by the function, also point it out.\" }}\n {{- \"You should only return the function call in tools call sections.\" }}\n {{- \"If you decide to invoke any of the function(s), you MUST put it in the format of [Function(arguments1={{params_name1: params_value1,params_name2: params_value2, ...}}, name1=function_name1), Function(arguments2={{params}}, name2=function_name2) , ...]\"}}\n {{- \"You SHOULD NOT include any other text in the response.\\nHere is a list of functions in JSON format that you can invoke.\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- \"<|eot_id|>\" }}\n\n\n{%- for message in messages %}\n {%- if not (message.role == 'tool') %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif message.role == \"tool\" %}\n {{- \"<|start_header_id|>tool<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}", + "clean_up_tokenization_spaces": true, + "eos_token": "<|eot_id|>", + "model_input_names": [ + "input_ids", + "attention_mask" + ], + "model_max_length": 131072, + "pad_token": "<|end_of_text|>", + "tokenizer_class": "PreTrainedTokenizerFast" +}