decode(outputs[0], skip_special_tokens=True)[len(input_text):]) This code will output the following result: for i in range(1, len(arr)): 3) Chat Model Inference from transformers import AutoTokenizer, AutoModelForCausalLM import torch tokenizer = AutoTokenizer.from_pretrained("deepseek-...
You can write latex quite nicely in Mathematica and to do vectors it's just \vec{stuff} which looks like; stuff→ May 17, 2012 #8 jwbales 8 0 In standard LaTeX you use \bar{X} X¯ or \overline{X} X―. As you can see, the \bar{X} is rather anemic and ...
---贴吧极速版 For UWP 分享回复赞 英语吧 没什么不得了o 【January·咨询】Can authors write their contribution in bullets是什么意思? 分享1赞 单片机学习吧 水瓶and处女 write_data(tab2[week][i]); 是什么意思? 分享2赞 mathematica吧 Lionel_M 新手Mathematica关于 Set::write的问题Set::write 这一句...
text for output in outputs] print(generated_text) 7. Q&A Could You Provide the tokenizer.model File for Model Quantization? DeepSeek Coder utilizes the HuggingFace Tokenizer to implement the Bytelevel-BPE algorithm, with specially designed pre-tokenizers to ensure optimal performance. Currently, ...
老师给了样本,奈何我 分享6赞 mathematica吧 xinghe2yu Tag Times in f\ x_ is Protected 是什么意思啊我输入函数求导的时候总是碰见如下问题,哪位懂的人能不能帮忙解答一下。 f (x_) := Sin[x] + 1/(x + 1) Integrat 分享2赞 按键精灵吧 xywliao 请问这问命令什么意思If 帐号 <> "" And ...
text for output in outputs] print(generated_text) Chat Completion from transformers import AutoTokenizer from vllm import LLM, SamplingParams tp_size = 4 # Tensor Parallelism sampling_params = SamplingParams(temperature=0.7, top_p=0.9, max_tokens=100) model_name = "deepseek-ai/deepseek-coder...
decode(outputs[0], skip_special_tokens=True)[len(input_text):]) This code will output the following result: for i in range(1, len(arr)): 3) Chat Model Inference from transformers import AutoTokenizer, AutoModelForCausalLM import torch tokenizer = AutoTokenizer.from_pretrained("deepseek-...
text for output in outputs] print(generated_text) 7. Q&A Could You Provide the tokenizer.model File for Model Quantization? DeepSeek Coder utilizes the HuggingFace Tokenizer to implement the Bytelevel-BPE algorithm, with specially designed pre-tokenizers to ensure optimal performance. Currently, ...
text for output in outputs] print(generated_text) 7. Q&A Could You Provide the tokenizer.model File for Model Quantization? DeepSeek Coder utilizes the HuggingFace Tokenizer to implement the Bytelevel-BPE algorithm, with specially designed pre-tokenizers to ensure optimal performance. Currently, ...
decode(outputs[0], skip_special_tokens=True)[len(input_text):]) This code will output the following result: for i in range(1, len(arr)): 3) Chat Model Inference from transformers import AutoTokenizer, AutoModelForCausalLM import torch tokenizer = AutoTokenizer.from_pretrained("deepseek-...