
# CLIP-Italian
CLIP Italian is a CLIP-like Model for Italian. The CLIP model (Contrastive Language–Image Pre-training) was developed by researchers at OpenAI and is able to efficiently learn visual concepts from natural language supervision. 

We fine-tuned a competitive Italian CLIP model with only ~1.4 million Italian image-text pairs. This model is part of the [Flax/Jax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.

## Training Data
We considered three main sources of data: 
- [WIT](https://github.com/google-research-datasets/wit)
- [MSCOCO-IT](https://github.com/crux82/mscoco-it)
- [Conceptual Captions](https://ai.google.com/research/ConceptualCaptions/)

## Training Procedure
Preprocessing, hardware used, hyperparameters...

## Evaluation Performance


## Limitations


## Usage


## Team members
- Federico Bianchi ([vinid](https://huggingface.co/vinid))
- Raphael Pisoni ([4rtemi5](https://huggingface.co/4rtemi5))
- Giuseppe Attanasio ([g8a9](https://huggingface.co/g8a9))
- Silvia Terragni ([silviatti](https://huggingface.co/silviatti))
- Dario Balestri ([D3Reo](https://huggingface.co/D3Reo))
- Gabriele Sarti ([gsarti](https://huggingface.co/gsarti))
- Sri Lakshmi ([srisweet](https://huggingface.co/srisweet))

## Useful links
- [CLIP Blog post](https://openai.com/blog/clip/)
- [CLIP paper](https://arxiv.org/abs/2103.00020)
- [Community Week README](https://github.com/huggingface/transformers/blob/master/examples/research_projects/jax-projects/README.md)
- [Community Week channel](https://discord.com/channels/858019234139602994/859711887520038933)
- [Hybrid CLIP example scripts](https://github.com/huggingface/transformers/tree/master/examples/research_projects/jax-projects/hybrid_clip)
- [Model Repository](https://huggingface.co/clip-italian/clip-italian-final/)
{"language": "it", "tags": ["italian", "bert", "vit", "vision"], "datasets": ["wit", "ctl/conceptualCaptions", "mscoco-it"]}
transformers jax hybrid-clip italian bert vit vision it dataset:wit dataset:ctl/conceptualCaptions dataset:mscoco-it arxiv:2103.00020 endpoints_compatible region:us
TAGS
#transformers #jax #hybrid-clip #italian #bert #vit #vision #it #dataset-wit #dataset-ctl/conceptualCaptions #dataset-mscoco-it #arxiv-2103.00020 #endpoints_compatible #region-us 


# CLIP-Italian
CLIP Italian is a CLIP-like Model for Italian. The CLIP model (Contrastive Language–Image Pre-training) was developed by researchers at OpenAI and is able to efficiently learn visual concepts from natural language supervision. 

We fine-tuned a competitive Italian CLIP model with only ~1.4 million Italian image-text pairs. This model is part of the Flax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.

## Training Data
We considered three main sources of data: 
- WIT
- MSCOCO-IT
- Conceptual Captions

## Training Procedure
Preprocessing, hardware used, hyperparameters...

## Evaluation Performance


## Limitations


## Usage


## Team members
- Federico Bianchi (vinid)
- Raphael Pisoni (4rtemi5)
- Giuseppe Attanasio (g8a9)
- Silvia Terragni (silviatti)
- Dario Balestri (D3Reo)
- Gabriele Sarti (gsarti)
- Sri Lakshmi (srisweet)

## Useful links
- CLIP Blog post
- CLIP paper
- Community Week README
- Community Week channel
- Hybrid CLIP example scripts
- Model Repository
# CLIP-Italian
CLIP Italian is a CLIP-like Model for Italian. The CLIP model (Contrastive Language–Image Pre-training) was developed by researchers at OpenAI and is able to efficiently learn visual concepts from natural language supervision. 

We fine-tuned a competitive Italian CLIP model with only ~1.4 million Italian image-text pairs. This model is part of the Flax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google. ## Training Data
We considered three main sources of data: 
- WIT
- MSCOCO-IT
- Conceptual Captions ## Training Procedure
Preprocessing, hardware used, hyperparameters... ## Evaluation Performance ## Limitations ## Usage ## Team members
- Federico Bianchi (vinid)
- Raphael Pisoni (4rtemi5)
- Giuseppe Attanasio (g8a9)
- Silvia Terragni (silviatti)
- Dario Balestri (D3Reo)
- Gabriele Sarti (gsarti)
- Sri Lakshmi (srisweet) ## Useful links
- CLIP Blog post
- CLIP paper
- Community Week README
- Community Week channel
- Hybrid CLIP example scripts
- Model Repository
TAGS
#transformers #jax #hybrid-clip #italian #bert #vit #vision #it #dataset-wit #dataset-ctl/conceptualCaptions #dataset-mscoco-it #arxiv-2103.00020 #endpoints_compatible #region-us 
 # CLIP-Italian
CLIP Italian is a CLIP-like Model for Italian. The CLIP model (Contrastive Language–Image Pre-training) was developed by researchers at OpenAI and is able to efficiently learn visual concepts from natural language supervision. 

We fine-tuned a competitive Italian CLIP model with only ~1.4 million Italian image-text pairs. This model is part of the Flax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google. ## Training Data
We considered three main sources of data: 
- WIT
- MSCOCO-IT
- Conceptual Captions ## Training Procedure
Preprocessing, hardware used, hyperparameters... ## Evaluation Performance ## Limitations ## Usage ## Team members
- Federico Bianchi (vinid)
- Raphael Pisoni (4rtemi5)
- Giuseppe Attanasio (g8a9)
- Silvia Terragni (silviatti)
- Dario Balestri (D3Reo)
- Gabriele Sarti (gsarti)
- Sri Lakshmi (srisweet) ## Useful links
- CLIP Blog post
- CLIP paper
- Community Week README
- Community Week channel
- Hybrid CLIP example scripts
- Model Repository
passage: TAGS
#transformers #jax #hybrid-clip #italian #bert #vit #vision #it #dataset-wit #dataset-ctl/conceptualCaptions #dataset-mscoco-it #arxiv-2103.00020 #endpoints_compatible #region-us 
# CLIP-Italian
CLIP Italian is a CLIP-like Model for Italian. The CLIP model (Contrastive Language–Image Pre-training) was developed by researchers at OpenAI and is able to efficiently learn visual concepts from natural language supervision. 

We fine-tuned a competitive Italian CLIP model with only ~1.4 million Italian image-text pairs. This model is part of the Flax/Jax Community Week, organized by HuggingFace and TPU usage sponsored by Google.## Training Data
We considered three main sources of data: 
- WIT
- MSCOCO-IT
- Conceptual Captions## Training Procedure
Preprocessing, hardware used, hyperparameters...## Evaluation Performance## Limitations## Usage## Team members
- Federico Bianchi (vinid)
- Raphael Pisoni (4rtemi5)
- Giuseppe Attanasio (g8a9)
- Silvia Terragni (silviatti)
- Dario Balestri (D3Reo)
- Gabriele Sarti (gsarti)
- Sri Lakshmi (srisweet)## Useful links
- CLIP Blog post
- CLIP paper
- Community Week README
- Community Week channel
- Hybrid CLIP example scripts
- Model Repository