Update README.md

README.md

@@ -6,137 +6,20 @@ tags:
 - sentence-transformers
 - sentence-similarity
 - feature-extraction
+new_version: nomic-ai/nomic-embed-text-v2-moe
 ---
 
-# SentenceTransformer based on nomic-ai/nomic-embed-text-v2-moe-unsupervised
 
-This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [nomic-ai/nomic-embed-text-v2-moe-unsupervised](https://huggingface.co/nomic-ai/nomic-embed-text-v2-moe-unsupervised). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+# nomic-embed-text-v2-moe-unsupervised
 
-## Model Details
+`nomic-embed-text-v2-moe-unsupervised` is multilingual MoE Text Embedding model. This is a checkpoint after contrastive pretraining from multi-stage contrastive training of the
+[final model](https://huggingface.co/nomic-ai/nomic-embed-text-v2-moe). 
 
-### Model Description
-- **Model Type:** Sentence Transformer
-- **Base model:** [nomic-ai/nomic-embed-text-v2-moe-unsupervised](https://huggingface.co/nomic-ai/nomic-embed-text-v2-moe-unsupervised) <!-- at revision e48a32f5906ed18933f85467e57c1dcc02ef401b -->
-- **Maximum Sequence Length:** 512 tokens
-- **Output Dimensionality:** 768 dimensions
-- **Similarity Function:** Cosine Similarity
-<!-- - **Training Dataset:** Unknown -->
-<!-- - **Language:** Unknown -->
-<!-- - **License:** Unknown -->
+If you want to use a model to extract embeddings, we suggest using [nomic-embed-text-v2-moe](https://huggingface.co/nomic-ai/nomic-embed-text-v2-moe)
 
-### Model Sources
 
-- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
-- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
-- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+# Join the Nomic Community
 
-### Full Model Architecture
-
-```
-SentenceTransformer(
-  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: NomicBertModel 
-  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
-  (2): Normalize()
-)
-```
-
-## Usage
-
-### Direct Usage (Sentence Transformers)
-
-First install the Sentence Transformers library:
-
-```bash
-pip install -U sentence-transformers
-```
-
-Then you can load this model and run inference.
-```python
-from sentence_transformers import SentenceTransformer
-
-# Download from the 🤗 Hub
-model = SentenceTransformer("nomic-ai/nomic-embed-text-v2-moe-unsupervised")
-# Run inference
-sentences = [
-    'The weather is lovely today.',
-    "It's so sunny outside!",
-    'He drove to the stadium.',
-]
-embeddings = model.encode(sentences)
-print(embeddings.shape)
-# [3, 768]
-
-# Get the similarity scores for the embeddings
-similarities = model.similarity(embeddings, embeddings)
-print(similarities.shape)
-# [3, 3]
-```
-
-<!--
-### Direct Usage (Transformers)
-
-<details><summary>Click to see the direct usage in Transformers</summary>
-
-</details>
--->
-
-<!--
-### Downstream Usage (Sentence Transformers)
-
-You can finetune this model on your own dataset.
-
-<details><summary>Click to expand</summary>
-
-</details>
--->
-
-<!--
-### Out-of-Scope Use
-
-*List how the model may foreseeably be misused and address what users ought not to do with the model.*
--->
-
-<!--
-## Bias, Risks and Limitations
-
-*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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-
-<!--
-### Recommendations
-
-*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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-
-## Training Details
-
-### Framework Versions
-- Python: 3.10.12
-- Sentence Transformers: 3.3.0
-- Transformers: 4.44.2
-- PyTorch: 2.4.1+cu121
-- Accelerate: 1.2.1
-- Datasets: 3.2.0
-- Tokenizers: 0.19.1
-
-## Citation
-
-### BibTeX
-
-<!--
-## Glossary
-
-*Clearly define terms in order to be accessible across audiences.*
--->
-
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-## Model Card Authors
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+- Nomic: [https://nomic.ai](https://nomic.ai)
+- Discord: [https://discord.gg/myY5YDR8z8](https://discord.gg/myY5YDR8z8)
+- Twitter: [https://twitter.com/nomic_ai](https://twitter.com/nomic_ai)