I am trying to make an AI app with langchain and Huggingface. I got the following error: { "error": "Could not load model paragon-AI/blip2-image-to-text with any of the following classes: (<class 'transformers.models.blip_2.modeling_blip_2.Blip2ForConditionalGenera...
Hi all. I believe the initial question is about #394 loading the pretrained model, directly downloaded from this repo. The first question is, how can someone load it, with huggingface, as it's seemingly easier to load a pretrained model...
import shutil import requests import torch # Download the .pth file locally url = "https://huggingface.co/Carve/u2net-universal/resolve/main/full_weights.pth" response = requests.get(url, stream=True) with open('full_weights.pth', 'wb') as out_file: shutil.copyfileobj(...
Issue you'd like to raise. I do not have access to huggingface.co in my environment, but I do have the Instructor model (hkunlp/instructor-large) saved locally. How do I utilize the langchain function HuggingFaceInstructEmbeddings to poi...
2. Installhuggingface-clitool. You can find the installation instructionshere huggingface-cli login After running the command, you’ll be prompted to enter your Hugging Face username and password. Make sure to enter the credentials associated with your Hugging Fa...
4. Remove the huggingface folder PressWindows+Eto openFile Explorer, paste the following path in the address bar while replacingUsernamewith the active user, and hitEnter:C:\Users\Username\.cache\huggingface PressCtrl+Ato select all the files, and hitDeleteto clear them. ...
Still not okay online, but I managed to do it locally git clonehttps://huggingface.co/bert-base-uncased #model = AutoModelWithHeads.from_pretrained(“bert-base-uncased”) model = AutoModelWithHeads.from_pretrained(BERT_LOCAL_PATH, local_files_only=True) ...
In the first test, we compared CoreWeave’s Tensorizer with SafeTensors and HuggingFace on Eleuther AI’s GPT-J-6B with NVIDIA A40 GPUs. In the chart below, you see that Tensorizer recorded the fastest model load time: CoreWeave’s Tensorizer: 8.22 sec. (median); 10.74 sec. (average...
I have downloaded the model from Hugging Face using snapshot_download, e.g., from huggingface_hub import snapshot_download snapshot_download(repo_id="facebook/nllb-200-distilled-600M", cache_dir="./") And when I list the directory, I see: ls ./models--facebook--nllb-...
# Load a remote model from HuggingFace's model hub reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2") # Save locally (in FARM format) reader.save("my_local_roberta_model") # Load locally (FARM format) reader_local = FARMReader(model_name_or_path="my_local_roberta...