访问Hugging Face 中的资源,需要使用Access Tokens,可以在 Hugging Face 设置页面(https://huggingface.co/settings/tokens)生成自己的token。 一旦你获得了token,可以有下面几种方法使用它: 一、直接在代码中传递token 类似如下代码,在代码中直接传递 Hugging Face 的 API 令牌。 from transformers import AutoProcessor...
in a private repository. It's also compatible with[Inference for PROs](https://huggingface.co/blog/inference-pro)curated list of powerful models with higher rate limits. Make sure to create your personal token first in your[User Access Tokens settings](https://huggingface.co/settings/tokens)....
Create an account on Huggingface.co and then create a Token in its settings -> Access Tokens. Add token to your ENV asHUGGINGFACE_TOKENor just hardcode in setup.py if testing. Add token arg in following places in setup.py hf_hub_download(repo_id=settings().llamacpp.llm_hf_repo_id,fil...
Note that it is difficult to achieve perfect PR curves, partially because for some movies, even the top 7https://huggingface.co/Jean-Baptiste/camembert-ner Methods Training Data Linear Proj ROC AUC Average Precision Cosine-Sim - TFM Decoder MAD-L-char TFM Decoder MovieNet TFM Decoder MovieNet...
This means that tokens that come after special tokens will not be properly handled. We recommend you to read the related pull request available at https://github.com/huggingface/transformers/pull/24565 You're using a T5TokenizerFast tokenizer. Please note that with a fast tokenizer, using the ...
docTokens[startOffset:startOffset+length] , biobert) )#stop when the whole document is processed (document has less than 512#or the last document slice was processed)ifstartOffset + length ==len(docTokens):breakstartOffset +=min(length, docStride) ...
(self, text, **kwargs) -> List[str]: """ Converts a string in a sequence of tokens (string), using the tokenizer. Split in words for word-based vocabulary or sub-words for sub-word-based vocabularies (BPE/SentencePieces/WordPieces). Do NOT take care of added tokens. """ return ...
-v $HOME/.cache/huggingface:/root/.cache/huggingface \ --env "HUGGING_FACE_HUB_TOKEN=$HUGGING_FACE_HUB_TOKEN" \ -p 23343:23333 \ --ipc=host \ --name internvl2_llama3_76b_lmdeploy \ internvl3 \ lmdeploy serve api_server OpenGVLab/InternVL2-Llama3-76B \ ...
"description": "The max number of tokens of a prompt.", "when": "DevChat.llmModel == 'OpenAI'" }, "DevChat.Access_Key_DevChat": { "type": "string", "default": "", "description": "DevChat's secret key for accessing multiple LLM models" }, "DevChat.Api_Key_OpenAI": { "...
--max-num-batched-tokens 102400 \ --max-model-len=102400 \ --quantization=experts_int8 \ --download-dir=/home/ubuntu/.cache/huggingface/hub &>> logs.vllm_server.jamba15mini.txt (base) ubuntu@compute-permanent-node-171:~$ docker logs jamba15mini ...