Hello. I have the below tasks for uploading however I am not sure if they are most effective way of doing This cell is used to upload single file into a repo with certain name from huggingface_hub import HfApi api = HfApi() api.upload_fi...
Select Docker as the Space SDK, and then click “Create Space”.Step 3: Clone repo Clone the Hugging Face repo in your command line (please remember to change the path to your own user name and Space name): git clone https://huggingface.co/spaces/sophiamyang/panel_example...
Yes, we have a sample in C# using Hugging Face in the repo. You can find it using the link below. https://github.com/microsoft/semantic-kernel/blob/main/samples/dotnet/kernel-syntax-examples/Example20_HuggingFace.cs regards, Nilesh Stay informed Get notified when new posts are published. ...
llm=HuggingFaceLLM(context_window=4096,max_new_tokens=256,generate_kwargs={"temperature":0.0,"do_sample":False},system_prompt=system_prompt,query_wrapper_prompt=query_wrapper_prompt,tokenizer_name="meta-llama/Llama-2-7b-chat-hf",model_name="meta-llama/Llama-2-7b-chat-hf",device_map="auto"...
$ git clone https://huggingface.co/spaces/kingabzpro/doc-qa-docker Powered By Copy and paste all the files from the project directory to the new repository: This is how your project directory should look with all the files. Always ensure you do not push the .env file, so add it to...
Alternatively, models can also be loaded from Hugging Face (requires pip install huggingface_hub). For image prediction: import torch from sam2.sam2_image_predictor import SAM2ImagePredictor predictor = SAM2ImagePredictor.from_pretrained("facebook/sam2-hiera-large") with torch.inference_mode(), ...
When put together, which we can see in the notebook filerun_any_space.ipynb, this allows for a very quick method for low coders to launch HuggingFace spaces in a Paperspace Notebook. Executing the shell script is shown here: !bash HF_to_PS.sh --f <paste_name_of_repo_here> ...
In the example above, we are using text-ada-001 model from OpenAI. If you would like to swap that for any open-source models from HuggingFace, it’s a simple change: API_KEY ="..." from langchain import HuggingFaceHub llm = HuggingFaceHub(repo_id = "google/flan-t5-xl", huggingface...
Additionally, we would save the data in the CSV format as we would need them for our fine-tuning. train.to_csv('train.csv', index = False) With the environment and the dataset ready, let’s try to use HuggingFace AutoTrain to fine-tune our LLM. ...
https://huggingface.co/learn/cookbook/en/rag_evaluation Llamaindex evals framework Top Comments in Forums There are no comments on this article yet. Start the Conversation Rate this tutorial Related Tutorial Getting started with MongoDB Atlas Search and Java Jul 30, 2024 | 7 min read Tutorial...