由于tokenizer的vocab_size是从pretrained model读取来的,而config的vocab_size是config.json中读取来的,而max_input_id表示加载到的数据中最大的词表数量 而bert base uncased的"vocab_size"为 30522,bert chinese的仅为21128,实际加载的各类训练数据等语料数据包含的vocab种类高达29486种,因此说明bert chinese的语料...
LLM何矗督Vocab size醒柔蛾攀蜓攘蚊夕 齐思用户 Invalid Date 写了一条评论 GPT-4的熟练程度并没有将UTF-8词元化作为最终的最佳方法。标记化是一种战略选择,取决于语言的复杂性和任务的要求。虽然UTF-8在GPT-4中可能表现出色,但当针对特定上下文进行优化时,BPE或WordPiece等其他方法可能会超越它。例如,BPE已...
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old_params =sum(p.numel() for p in model.parameters())print("Total params of original model: %.2fM"% (old_params /1e6)) # 对于新词表中的每个token,取出其对应的权重,复制到新模型中 vocab_size =len(new_tokenizer) hidden_size = model.config.hidden_size new_embeds = torch.nn.Embedding...
@@ -243,8 +243,7 @@ def _set_vocab_gpt2(self): for i in range(vocab_size): if i not in reverse_vocab: pad_token = f"[PAD{i}]".encode('utf-8') tokens.append(bytearray(pad_token)) tokens.append(f"[PAD{i}]") toktypes.append(gguf.TokenType.USER_DEFINED) elif reverse_vo...
// expand your vocabulary in a new language quickly through curated chatgpt-4o generated words // the app improves vocabulary knowledge through rapid repetition in the visual and auditory domain // once you master each set of new words, chatgpt will add more, pushing your memorization skills ...
Our sentences are generated by ChatGPT to be interesting, challenging, and appropriate for any level. By reading full sentences in your target language, you acquire vocab and grammar naturally and in context. Why use Yap? Two critical keys to learning a language to fluency is (1) consistent ...
The offline & original crx file ofVocaby v1.3.1was fully archived from the web store server and is for home or personal use only. You could learn more about theVocabyor proceed to install it to your web browser.
\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)", }; break; case LLAMA_VOCAB_PRE_TYPE_GPT2: case LLAMA_VOCAB_PRE_TYPE_MPT: case LLAMA_VOCAB_PRE_TYPE_OLMO: case LLAMA_VOCAB_PRE_TYPE_JAIS: regex_exprs = { "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+|...
use 2 GPUs to parallelize the model tensor, and 4 GPUs to parallelize the model pipeline. The present function will @@ -84,49 +82,44 @@ def initialize_model_parallel(tensor_model_parallel_size_=1, with a total of 16 GPUs, rank 0 to 7 belong to the first box and ranks 8 to 15 ...