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HuggingFaceDocBuilderย
updated
a
dataset
about 3 hours ago
HuggingFaceDocBuilderย
updated
a
dataset
about 18 hours ago
Post
869
Nice to see day 1 support of Falcon 3 on Gaudi with Optimum Habana!
๐ https://www.intel.com/content/www/us/en/developer/articles/technical/intel-ai-solutions-support-falcon-3-fdn-models.html
๐ https://www.intel.com/content/www/us/en/developer/articles/technical/intel-ai-solutions-support-falcon-3-fdn-models.html
Post
1617
๐ SUPER BLACK FRIDAY DEAL ๐
Train almost any model on a variety of tasks such as llm finetuning, text classification/regression, summarization, question answering, image classification/regression, object detection, tabular data, etc for FREE using AutoTrain locally. ๐ฅ
https://github.com/huggingface/autotrain-advanced
Train almost any model on a variety of tasks such as llm finetuning, text classification/regression, summarization, question answering, image classification/regression, object detection, tabular data, etc for FREE using AutoTrain locally. ๐ฅ
https://github.com/huggingface/autotrain-advanced
Post
5410
INTRODUCING Hugging Face AutoTrain Client ๐ฅ
Fine-tuning models got even easier!!!!
Now you can fine-tune SOTA models on all compatible dataset-model pairs on Hugging Face Hub using Python on Hugging Face Servers. Choose from a number of GPU flavors, millions of models and dataset pairs and 10+ tasks ๐ค
To try, install autotrain-advanced using pip. You can ignore dependencies and install without --no-deps and then you'd need to install some dependencies by hand.
"pip install autotrain-advanced"
Github repo: https://github.com/huggingface/autotrain-advanced
Fine-tuning models got even easier!!!!
Now you can fine-tune SOTA models on all compatible dataset-model pairs on Hugging Face Hub using Python on Hugging Face Servers. Choose from a number of GPU flavors, millions of models and dataset pairs and 10+ tasks ๐ค
To try, install autotrain-advanced using pip. You can ignore dependencies and install without --no-deps and then you'd need to install some dependencies by hand.
"pip install autotrain-advanced"
Github repo: https://github.com/huggingface/autotrain-advanced
- 6 replies
abhishekย
authored
a
paper
2 months ago
Post
1378
Interested in performing inference with an ONNX model?โก๏ธ
The Optimum docs about model inference with ONNX Runtime is now much clearer and simpler!
You want to deploy your favorite model on the hub but you don't know how to export it to the ONNX format? You can do it in one line of code as follows:
Check out the whole guide ๐ https://huggingface.co/docs/optimum/onnxruntime/usage_guides/models
The Optimum docs about model inference with ONNX Runtime is now much clearer and simpler!
You want to deploy your favorite model on the hub but you don't know how to export it to the ONNX format? You can do it in one line of code as follows:
from optimum.onnxruntime import ORTModelForSequenceClassification
# Load the model from the hub and export it to the ONNX format
model_id = "distilbert-base-uncased-finetuned-sst-2-english"
model = ORTModelForSequenceClassification.from_pretrained(model_id, export=True)Check out the whole guide ๐ https://huggingface.co/docs/optimum/onnxruntime/usage_guides/models
Post
2790
What a great milestone to celebrate! The huggingface_hub library is slowly becoming a cornerstone of the Python ML ecosystem when it comes to interacting with the
@huggingface
Hub. It wouldn't be there without the hundreds of community contributions and feedback! No matter if you are loading a model, sharing a dataset, running remote inference or starting jobs on our infra, you are for sure using it! And this is only the beginning so give a star if you wanna follow the project ๐ https://github.com/huggingface/huggingface_hub
- 1 reply
Post
4573
๐ Exciting News! ๐
We've just released ๐๐๐๐๐๐๐๐๐๐๐_๐๐๐ v0.25.0 and it's packed with powerful new features and improvements!
โจ ๐ง๐ผ๐ฝ ๐๐ถ๐ด๐ต๐น๐ถ๐ด๐ต๐๐:
โข ๐ ๐จ๐ฝ๐น๐ผ๐ฎ๐ฑ ๐น๐ฎ๐ฟ๐ด๐ฒ ๐ณ๐ผ๐น๐ฑ๐ฒ๐ฟ๐ with ease using
โข ๐ ๐ฆ๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ฃ๐: new search filters (gated status, inference status) and fetch trending score.
โข โก๐๐ป๐ณ๐ฒ๐ฟ๐ฒ๐ป๐ฐ๐ฒ๐๐น๐ถ๐ฒ๐ป๐: major improvements simplifying chat completions and handling async tasks better.
Weโve also introduced tons of bug fixes and quality-of-life improvements - thanks to the awesome contributions from our community! ๐ช
๐ก Check out the release notes: Wauplin/huggingface_hub#8
Want to try it out? Install the release with:
We've just released ๐๐๐๐๐๐๐๐๐๐๐_๐๐๐ v0.25.0 and it's packed with powerful new features and improvements!
โจ ๐ง๐ผ๐ฝ ๐๐ถ๐ด๐ต๐น๐ถ๐ด๐ต๐๐:
โข ๐ ๐จ๐ฝ๐น๐ผ๐ฎ๐ฑ ๐น๐ฎ๐ฟ๐ด๐ฒ ๐ณ๐ผ๐น๐ฑ๐ฒ๐ฟ๐ with ease using
huggingface-cli upload-large-folder. Designed for your massive models and datasets. Much recommended if you struggle to upload your Llama 70B fine-tuned model ๐คกโข ๐ ๐ฆ๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ฃ๐: new search filters (gated status, inference status) and fetch trending score.
โข โก๐๐ป๐ณ๐ฒ๐ฟ๐ฒ๐ป๐ฐ๐ฒ๐๐น๐ถ๐ฒ๐ป๐: major improvements simplifying chat completions and handling async tasks better.
Weโve also introduced tons of bug fixes and quality-of-life improvements - thanks to the awesome contributions from our community! ๐ช
๐ก Check out the release notes: Wauplin/huggingface_hub#8
Want to try it out? Install the release with:
pip install huggingface_hub==0.25.0
- 1 reply
Post
1854
๐จ NEW TASK ALERT ๐จ
Extractive Question Answering: because sometimes generative is not all you need ๐
AutoTrain is the only open-source, no code solution to offer so many tasks across different modalities. Current task count: 23 ๐
Check out the blog post on getting started with this task: https://huggingface.co/blog/abhishek/extractive-qa-autotrain
Extractive Question Answering: because sometimes generative is not all you need ๐
AutoTrain is the only open-source, no code solution to offer so many tasks across different modalities. Current task count: 23 ๐
Check out the blog post on getting started with this task: https://huggingface.co/blog/abhishek/extractive-qa-autotrain
Post
1984
๐ Just released version 0.24.0 of the ๐๐๐๐๐๐๐๐๐๐๐_๐๐๐ Python library!
Exciting updates include:
โก InferenceClient is now a drop-in replacement for OpenAI's chat completion!
โจ Support for response_format, adapter_id , truncate, and more in InferenceClient
๐พ Serialization module with a save_torch_model helper that handles shared layers, sharding, naming convention, and safe serialization. Basically a condensed version of logic scattered across safetensors, transformers , accelerate
๐ Optimized HfFileSystem to avoid getting rate limited when browsing HuggingFaceFW/fineweb
๐จ HfApi & CLI improvements: prevent empty commits, create repo inside resource group, webhooks API, more options in the Search API, etc.
Check out the full release notes for more details:
Wauplin/huggingface_hub#7
๐
Exciting updates include:
โก InferenceClient is now a drop-in replacement for OpenAI's chat completion!
โจ Support for response_format, adapter_id , truncate, and more in InferenceClient
๐พ Serialization module with a save_torch_model helper that handles shared layers, sharding, naming convention, and safe serialization. Basically a condensed version of logic scattered across safetensors, transformers , accelerate
๐ Optimized HfFileSystem to avoid getting rate limited when browsing HuggingFaceFW/fineweb
๐จ HfApi & CLI improvements: prevent empty commits, create repo inside resource group, webhooks API, more options in the Search API, etc.
Check out the full release notes for more details:
Wauplin/huggingface_hub#7
๐
- 6 replies
Post
3355
๐ I'm excited to announce that huggingface_hub's InferenceClient now supports OpenAI's Python client syntax! For developers integrating AI into their codebases, this means you can switch to open-source models with just three lines of code. Here's a quick example of how easy it is.
Why use the InferenceClient?
๐ Seamless transition: keep your existing code structure while leveraging LLMs hosted on the Hugging Face Hub.
๐ค Direct integration: easily launch a model to run inference using our Inference Endpoint service.
๐ Stay Updated: always be in sync with the latest Text-Generation-Inference (TGI) updates.
More details in https://huggingface.co/docs/huggingface_hub/main/en/guides/inference#openai-compatibility
Why use the InferenceClient?
๐ Seamless transition: keep your existing code structure while leveraging LLMs hosted on the Hugging Face Hub.
๐ค Direct integration: easily launch a model to run inference using our Inference Endpoint service.
๐ Stay Updated: always be in sync with the latest Text-Generation-Inference (TGI) updates.
More details in https://huggingface.co/docs/huggingface_hub/main/en/guides/inference#openai-compatibility
-
- 3 replies
Post
3317
You can now train/finetune custom sentence transformer embedding models using AutoTrain. Read blog: https://huggingface.co/blog/abhishek/finetune-custom-embeddings-autotrain
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- 2 replies
Post
2935
๐จ NEW TASK ALERT ๐จ
๐ AutoTrain now supports Object Detection! ๐
Transform your projects with these powerful new features:
๐น Fine-tune any supported model from the Hugging Face Hub
๐น Seamless logging with TensorBoard or W&B
๐น Support for local and hub datasets
๐น Configurable training for tailored results
๐น Train locally or leverage Hugging Face Spaces
๐น Deployment-ready with API inference or Hugging Face endpoints
AutoTrain: https://hf.co/autotrain
๐ AutoTrain now supports Object Detection! ๐
Transform your projects with these powerful new features:
๐น Fine-tune any supported model from the Hugging Face Hub
๐น Seamless logging with TensorBoard or W&B
๐น Support for local and hub datasets
๐น Configurable training for tailored results
๐น Train locally or leverage Hugging Face Spaces
๐น Deployment-ready with API inference or Hugging Face endpoints
AutoTrain: https://hf.co/autotrain
Post
3062
๐๐๐๐ Introducing AutoTrain Configs! ๐๐๐๐
Now you can train models using yaml config files! ๐ฅ These configs are easy to understand and are not at all overwhelming. So, even a person with almost zero knowledge of machine learning can train state of the art models without writing any code. Check out example configs in the config directory of autotrain-advanced github repo and feel free to share configs by creating a pull request ๐ค
Github repo: https://github.com/huggingface/autotrain-advanced
Now you can train models using yaml config files! ๐ฅ These configs are easy to understand and are not at all overwhelming. So, even a person with almost zero knowledge of machine learning can train state of the art models without writing any code. Check out example configs in the config directory of autotrain-advanced github repo and feel free to share configs by creating a pull request ๐ค
Github repo: https://github.com/huggingface/autotrain-advanced
- 2 replies
Post
1827
๐ Just released version 0.23.0 of the huggingface_hub Python library!
Exciting updates include:
๐ Seamless download to local dir!
๐ก Grammar and Tools in InferenceClient!
๐ Documentation full translated to Korean!
๐ฅ User API: get likes, upvotes, nb of repos, etc.!
๐งฉ Better model cards and encoding for ModelHubMixin!
Check out the full release notes for more details:
Wauplin/huggingface_hub#6
๐
Exciting updates include:
๐ Seamless download to local dir!
๐ก Grammar and Tools in InferenceClient!
๐ Documentation full translated to Korean!
๐ฅ User API: get likes, upvotes, nb of repos, etc.!
๐งฉ Better model cards and encoding for ModelHubMixin!
Check out the full release notes for more details:
Wauplin/huggingface_hub#6
๐
Post
3072
Post
2371
Trained another version of llama3-8b-instruct which beats the base model. This time without losing too many points on gsm8k benchmark. Again, using AutoTrain ๐ฅ pip install autotrain-advanced
Trained model: abhishek/autotrain-llama3-orpo-v2
Trained model: abhishek/autotrain-llama3-orpo-v2
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- 1 reply