The Lucie-7B LLM and the Lucie Training Dataset: Open resources for multilingual language generation
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jplorre
authored
a
paper
about 6 hours ago
prithivMLmods
posted
an
update
1 day ago
Post
1330
Dropping Downstream tasks using newly initialized parameters and weights ([classifier.bias & weights]) support domain-specific 𝗶𝗺𝗮𝗴𝗲 𝗰𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻. Based on siglip2-base-patch16-224 and DomainNet (single-domain, multi-source adaptation), with Fashion-MNIST for experimental testing. 🧤☄️
Fashion-Mnist : prithivMLmods/Fashion-Mnist-SigLIP2
Multisource-121 : prithivMLmods/Multisource-121-DomainNet
Painting-126 : prithivMLmods/Painting-126-DomainNet
Sketch-126 : prithivMLmods/Sketch-126-DomainNet
Clipart-126 : prithivMLmods/Clipart-126-DomainNet
Models are trained with different parameter settings for experimental purposes only, with the intent of further development. Refer to the model page below for instructions on running it with Transformers 🤗.
Collection : prithivMLmods/domainnet-0324-67e0e3c934c03cc40c6c8782
Citations : SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/pdf/2502.14786 & Moment Matching for Multi-Source Domain Adaptation : https://arxiv.org/pdf/1812.01754
Fashion-Mnist : prithivMLmods/Fashion-Mnist-SigLIP2
Multisource-121 : prithivMLmods/Multisource-121-DomainNet
Painting-126 : prithivMLmods/Painting-126-DomainNet
Sketch-126 : prithivMLmods/Sketch-126-DomainNet
Clipart-126 : prithivMLmods/Clipart-126-DomainNet
Models are trained with different parameter settings for experimental purposes only, with the intent of further development. Refer to the model page below for instructions on running it with Transformers 🤗.
Collection : prithivMLmods/domainnet-0324-67e0e3c934c03cc40c6c8782
Citations : SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/pdf/2502.14786 & Moment Matching for Multi-Source Domain Adaptation : https://arxiv.org/pdf/1812.01754
louisbrulenaudet
posted
an
update
2 days ago
Post
677
I’ve just released logfire-callback on PyPI, designed to facilitate monitoring of Hugging Face Transformer training loops using Pydantic Logfire 🤗
The callback will automatically log training start with configuration parameters, periodic metrics and training completion ⏱️
Install the package using pip:
First, ensure you have a Logfire API token and set it as an environment variable:
Then use the callback in your training code:
If you have any feedback, please reach out at @louisbrulenaudet
The callback will automatically log training start with configuration parameters, periodic metrics and training completion ⏱️
Install the package using pip:
pip install logfire-callbackFirst, ensure you have a Logfire API token and set it as an environment variable:
export LOGFIRE_TOKEN=your_logfire_tokenThen use the callback in your training code:
from transformers import Trainer, TrainingArguments
from logfire_callback import LogfireCallback
# Initialize your model, dataset, etc.
training_args = TrainingArguments(
output_dir="./results",
num_train_epochs=3,
# ... other training arguments
)
trainer = Trainer(
model=model,
args=training_args,
train_dataset=train_dataset,
callbacks=[LogfireCallback()] # Add the Logfire callback here
)
trainer.train()If you have any feedback, please reach out at @louisbrulenaudet
juliehunter
updated
a
model
4 days ago
prithivMLmods
posted
an
update
5 days ago
Post
2171
Play with Orpheus TTS, a Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation. This model has been fine-tuned to deliver human-level speech synthesis 🔥🗣️
👉GitHub [ Demo ] : https://github.com/PRITHIVSAKTHIUR/Orpheus-TTS-Edge
Demo supporting both text-to-speech and text-to-llm responses in speech.
> voice: tara, dan, emma, josh
> emotion: <laugh>, <chuckle>, <sigh>, <cough>, <sniffle>, <groan>, <yawn>, <gasp>.
🥠Orpheus-3b-0.1-ft
Model Page: canopylabs/orpheus-3b-0.1-ft
🥠Orpheus-3b-0.1-ft
Colab Inference Notebook: https://colab.research.google.com/drive/1KhXT56UePPUHhqitJNUxq63k-pQomz3N?usp=sharing
🥠Finetune [ orpheus-3b-0.1-pretrained ]
Resource: https://github.com/canopyai/Orpheus-TTS/tree/main/finetune
🥠Model-releases:
https://canopylabs.ai/model-releases
👉GitHub [ Demo ] : https://github.com/PRITHIVSAKTHIUR/Orpheus-TTS-Edge
Demo supporting both text-to-speech and text-to-llm responses in speech.
> voice: tara, dan, emma, josh
> emotion: <laugh>, <chuckle>, <sigh>, <cough>, <sniffle>, <groan>, <yawn>, <gasp>.
🥠Orpheus-3b-0.1-ft
Model Page: canopylabs/orpheus-3b-0.1-ft
🥠Orpheus-3b-0.1-ft
Colab Inference Notebook: https://colab.research.google.com/drive/1KhXT56UePPUHhqitJNUxq63k-pQomz3N?usp=sharing
🥠Finetune [ orpheus-3b-0.1-pretrained ]
Resource: https://github.com/canopyai/Orpheus-TTS/tree/main/finetune
🥠Model-releases:
https://canopylabs.ai/model-releases
- 1 reply
juliehunter
updated
a
dataset
6 days ago
juliehunter
updated
a
model
6 days ago
Jeronymous
authored
a
paper
6 days ago
fix typo
#1 opened 10 days ago
by
davebulaval
juliehunter
updated
a
collection
7 days ago
juliehunter
updated
a
model
7 days ago
Question about license
2
#3 opened 7 days ago
by
raymondng76
prithivMLmods
posted
an
update
11 days ago
Post
920
Hey Guys! One Small Announcement 🤗
Stranger Zone now accepts LoRA requests!
✍️Request : strangerzonehf/Request-LoRA [ or ] strangerzonehf/Request-LoRA#1
Page : https://huggingface.co/strangerzonehf
Describe the artistic properties by posting sample images or links to similar images in the request discussion. If the adapters you're asking for are truly creative and safe for work, I'll train and upload the LoRA to the Stranger Zone repo!
Thank you!
Stranger Zone now accepts LoRA requests!
✍️Request : strangerzonehf/Request-LoRA [ or ] strangerzonehf/Request-LoRA#1
Page : https://huggingface.co/strangerzonehf
Describe the artistic properties by posting sample images or links to similar images in the request discussion. If the adapters you're asking for are truly creative and safe for work, I'll train and upload the LoRA to the Stranger Zone repo!
Thank you!
prithivMLmods
posted
an
update
13 days ago
Post
2471
Gemma-3-4B : Image and Video Inference 🖼️🎥
🧤Space: prithivMLmods/Gemma-3-Multimodal
🥠Git : https://github.com/PRITHIVSAKTHIUR/Gemma-3-Multimodal
@gemma3 : {Tag + Space_+ 'prompt'}
@video-infer : {Tag + Space_+ 'prompt'}
+ Gemma3-4B : google/gemma-3-4b-it
+ By default, it runs : prithivMLmods/Qwen2-VL-OCR-2B-Instruct
Gemma 3 Technical Report : https://storage.googleapis.com/deepmind-media/gemma/Gemma3Report.pdf
🧤Space: prithivMLmods/Gemma-3-Multimodal
🥠Git : https://github.com/PRITHIVSAKTHIUR/Gemma-3-Multimodal
@gemma3 : {Tag + Space_+ 'prompt'}
@video-infer : {Tag + Space_+ 'prompt'}
+ Gemma3-4B : google/gemma-3-4b-it
+ By default, it runs : prithivMLmods/Qwen2-VL-OCR-2B-Instruct
Gemma 3 Technical Report : https://storage.googleapis.com/deepmind-media/gemma/Gemma3Report.pdf
- 1 reply
prithivMLmods
posted
an
update
14 days ago
Post
2778
Variable Demo for Two Image-to-Text-to-Text Multimodals 🌠
📜Space: prithivMLmods/Multimodal-OCR
By default, it will use:
prithivMLmods/Qwen2-VL-OCR-2B-Instruct or
prithivMLmods/Qwen2-VL-OCR2-2B-Instruct
To trigger Aya-Vision's 8B by @aya-vision , use the prompt:
CohereForAI/aya-vision-8b
📜Space: prithivMLmods/Multimodal-OCR
By default, it will use:
prithivMLmods/Qwen2-VL-OCR-2B-Instruct or
prithivMLmods/Qwen2-VL-OCR2-2B-Instruct
To trigger Aya-Vision's 8B by @aya-vision , use the prompt:
CohereForAI/aya-vision-8b
Post
1160
🙋🏻♂️Hey there folks,
Did you know that you can use ModernBERT to detect model hallucinations ?
Check out the Demo : Tonic/hallucination-test
See here for Medical Context Demo : MultiTransformer/tonic-discharge-guard
check out the model from KRLabs : KRLabsOrg/lettucedect-large-modernbert-en-v1
and the library they kindly open sourced for it : https://github.com/KRLabsOrg/LettuceDetect
👆🏻if you like this topic please contribute code upstream 🚀
Did you know that you can use ModernBERT to detect model hallucinations ?
Check out the Demo : Tonic/hallucination-test
See here for Medical Context Demo : MultiTransformer/tonic-discharge-guard
check out the model from KRLabs : KRLabsOrg/lettucedect-large-modernbert-en-v1
and the library they kindly open sourced for it : https://github.com/KRLabsOrg/LettuceDetect
👆🏻if you like this topic please contribute code upstream 🚀
- 2 replies
guokan-shang
authored
a
paper
18 days ago
ZennyKenny
posted
an
update
20 days ago
Post
515
It took me a while, but I've finally got it working:
ZennyKenny/note-to-text
Using a Meta LLaMa checkpoint from Unsloth and some help from the HF community, you can capture handwritten notes and convert them into digital format in just a few second.
Really exciting times for AI builders on Hugging Face.
Using a Meta LLaMa checkpoint from Unsloth and some help from the HF community, you can capture handwritten notes and convert them into digital format in just a few second.
Really exciting times for AI builders on Hugging Face.
-
- 2 replies
Post
701
Powered by
KRLabsOrg/lettucedect-large-modernbert-en-v1 from KRLabsOrg.
Detect hallucinations in answers based on context and questions using ModernBERT with 8192-token context support!
### Model Details
- **Model Name**: [lettucedect-large-modernbert-en-v1]( KRLabsOrg/lettucedect-large-modernbert-en-v1)
- **Organization**: [KRLabsOrg](https://huggingface.co/KRLabsOrg)
- **Github**: [https://github.com/KRLabsOrg/LettuceDetect](https://github.com/KRLabsOrg/LettuceDetect)
- **Architecture**: ModernBERT (Large) with extended context support up to 8192 tokens
- **Task**: Token Classification / Hallucination Detection
- **Training Dataset**: [RagTruth]( wandb/RAGTruth-processed)
- **Language**: English
- **Capabilities**: Detects hallucinated spans in answers, provides confidence scores, and calculates average confidence across detected spans.
LettuceDetect excels at processing long documents to determine if an answer aligns with the provided context, making it a powerful tool for ensuring factual accuracy.
Detect hallucinations in answers based on context and questions using ModernBERT with 8192-token context support!
### Model Details
- **Model Name**: [lettucedect-large-modernbert-en-v1]( KRLabsOrg/lettucedect-large-modernbert-en-v1)
- **Organization**: [KRLabsOrg](https://huggingface.co/KRLabsOrg)
- **Github**: [https://github.com/KRLabsOrg/LettuceDetect](https://github.com/KRLabsOrg/LettuceDetect)
- **Architecture**: ModernBERT (Large) with extended context support up to 8192 tokens
- **Task**: Token Classification / Hallucination Detection
- **Training Dataset**: [RagTruth]( wandb/RAGTruth-processed)
- **Language**: English
- **Capabilities**: Detects hallucinated spans in answers, provides confidence scores, and calculates average confidence across detected spans.
LettuceDetect excels at processing long documents to determine if an answer aligns with the provided context, making it a powerful tool for ensuring factual accuracy.
prithivMLmods
posted
an
update
20 days ago
Post
4942
SigLIP2 Image Classification 🧤
> https://huggingface.co/blog/prithivMLmods/siglip2-finetune-image-classification
> https://huggingface.co/blog/prithivMLmods/siglip2-finetune-image-classification