请运行huggingface-cli login或设置HF_TOKEN环境变量,其中包含你的一个访问令牌。你可以在你的设置页面(https://huggingface.co/settings/tokens)生成一个新的令牌。然后,点击gr.LoginButton将登录你的本地HuggingFace个人资料,允许你在部署到Space之前使用你的Hugging Face账户调试你的应用。 OAuth(使用外部提供商) 在...
("/path/to/your/local/training-images.zip","rb"),"steps":1000,"hf_token":"YOUR_HUGGING_FACE_TOKEN",# optional"hf_repo_id":"YOUR_HUGGING_FACE_REPO_ID",# optional},destination=f"{model.owner}/{model.name}")print(f"Training started:{training.status}")print(f"Training URL: https:/...
Now, download the Mistral 7BGGUFteacher/critic model that we will be using in SDG. Be sure to add your Hugging Face token: ilab model download --hf-token--repository TheBloke/Mistral-7B-Instruct-v0.2-GGUF --filename mistral-7b-instruct-v0.2.Q4_K_M.gguf Training Synthetic data ...
一旦用户使用他们的HF账户登录,你可以通过在任何Gradio函数中添加一个类型为gr.OAuthProfile的参数来检索他们的个人资料。个人资料将自动作为参数值注入。如果你想代表用户执行操作(例如列出用户的私有仓库、创建仓库等),你可以通过添加一个类型为gr.OAuthToken的参数来检索用户令牌。你必须在Space元数据中定义你将使用的...
llm.google_palm import GooglePalm # GooglePalm llm = GooglePalm(api_token="YOUR_Google_API_KEY") # Starcoder llm = Starcoder(api_token="YOUR_HF_API_KEY") # Falcon llm = Falcon(api_token="YOUR_HF_API_KEY") Powered By You can also set up a .env file and avoid setting up api...
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["special_tokens_map.json","generation_config.json","tokenizer_config.json","model.safetensors","eval_results.json","tokenizer.model","tokenizer.json","config.json"]forfilenameinrequired_files:download_location=hf_hub_download(repo_id=huggingface_model,filename=filename,token=HUGGING_FACE_API_...
make sure you have a Hugging Face token ready to use. If you don’t, head over tohuggingface.co, click on your profile image, then clickAccess Tokens. Create a newwritetoken for your notebooks. You will use this token at the beginning of the course notebooks to log into the HF API....
This directly improves the inference speed, first-token latency, memory usage, and power consumption. As a result, MiniCPM-V 2.6 can efficiently support real-time video understanding on end-side devices such as iPad. 💫 Easy Usage. MiniCPM-V 2.6 can be easily used in various ways: (1)...
“experts” relevant to the input. Think of it as a team of specialists—each expert focuses on a specific problem, while the rest remain idle. This approach slashes computational waste. For example, DeepSeek-V3 activates just 37 billion parameters per token, compared to GPT-4’s dense ...