# for each encoding, print the # of tokens, the token integers, and the token bytes for encoding_name in ["gpt2", "p50k_base", "cl100k_base"]: encoding = tiktoken.get_encoding(encoding_name) token_integers = encoding.encode(example_string) num_tokens = len(token_integers) token_byt...
get_encoding("cl100k_base" if model_name == "gpt-3.5-turbo" else "p50k_base") model_context_size = ( 4097 if model_name == "gpt-3.5-turbo" else llm.modelname_to_contextsize(model_name) ) text_max_length = model_context_size - len( tokenizer.encode( prompt_template.format(num_...
"""encoding=tiktoken.get_encoding(encoding_name)num_tokens=len(encoding.encode(string))returnnum_tokensif__name__=='__main__':print("Hello, world!")string="Hello, world!"encoding_name="cl100k_base"num_tokens=num_tokens_from_string(string,encoding_name)print(f"{string}has{num_tokens}tok...
cl100k_base = tiktoken.get_encoding("cl100k_base") # In production, load the arguments directly instead of accessing private attributes # See openai_public.py for examples of arguments for specific encodings enc = tiktoken.Encoding( # If you're changing the set of special tokens, make sure...
encoder=tiktoken.get_encoding("cl100k_base")text="Hello, this is a test text."tokens=encoder.encode(text)print(f'Tokens:{tokens}') 1. 2. 3. 4. 5. 6. 为了可视化我们的测试路径,我可以使用旅行图展示验证过程: Usertiktoken 测试准备 ...
get_encoding("cl100k_base") # 示例编码规则 计算token 数量: tokens = encoding.encode("通义千问具有强大的能力。") print(f"Token 数量: {len(tokens)}") 对于qwen-14b,如果需要适配 tiktoken,可以尝试以下方法: - 使用 dashscope 提供的 tokenizer 输出结果,手动映射到 tiktoken 的编码规则。 - ...
import { get_encoding, init } from "tiktoken/init"; async function main() { const wasm = "..."; // fetch the WASM binary somehow await init((imports) => WebAssembly.instantiate(wasm, imports)); const encoding = get_encoding("cl100k_base"); const tokens = encoding.encode("hello wor...
We get <Encoding 'cl100k_base'> as an output. Before we get to working with Tiktoken directly, I want to mention that OpenAI has a tokenization web app where you can see how different strings are tokenized—you can access it here. There is also a third-party online tokenizer, Tiktoken...
Step 2. Load an encoding tiktoken.get_encoding method returns the relevant encoding encoding = tiktoken.get_encoding("cl100k_base") encoding Powered By Output: >>> <Encoding 'cl100k_base'> Alternatively, you can also load it from the model name by using the tiktoken.encoding_for_model...
for encoding_name in ["r50k_base", "p50k_base", "cl100k_base", "o200k_base"]: encoding = tiktoken.get_encoding(encoding_name) token_integers = encoding.encode(example_string) num_tokens = len(token_integers) token_bytes = [encoding.decode_single_token_bytes(token) for token in token...