FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. Financial PhraseBank by Malo et al. (2014) is used for fine-tuning. For more details, please see the paper FinBERT: Financial Sentiment Analysis with Pre-trained Language Models and our related blog post on Medium. The model will give softmax outputs for three labels: positive, negative or neutral. About Prosus Prosus is a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally…
Open-weight model · Text classification
ms-marco-MiniLM-L-6-v2
by Joshua Xenova/ms-marco-MiniLM-L-6-v2
https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-6-v2 with ONNX weights to be compatible with Transformers.js.
Parameters—
Context512
Weights345.8 MB
License—
AccessOpen weights
Monthly Downloads1.1M
Model Card
https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-6-v2 with ONNX weights to be compatible with Transformers.js. If you haven't already, you can install the Transformers.js JavaScript library from NPM using: Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).
Excerpt from the card by Joshua.
Configuration
- Architecture
- BertForSequenceClassification
- Context length (tokens)
- 512
- Layers
- 6
- Hidden size
- 384
- Feed-forward size
- 1,536
- Attention heads
- 12
- Vocabulary size
- 30,522
- Model type
- bert
Identity and Version
- Repository
- Xenova/ms-marco-MiniLM-L-6-v2
- Publisher
- Joshua
- Task
- Text classification
- Modality
- Text
- Library
- transformers.js
- Parameters
- Not stated by the source
- Languages
- Not stated by the source
- Revision
- a09144355adeed5f58c8ed011d209bf8ee5a1fec
- First published
- 2024-01-04
- Last updated
- 2025-06-30
Files and Weights
16 files, 346.8 MB in total. The weights are 8 files totalling 345.8 MB in onnx.
Weights8 files · 345.8 MB
Configuration3 files · 1.7 KB
Tokenizer3 files · 944.1 KB
Documentation1 file · 1.8 KB
Repository1 file · 1.5 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| onnx/model.onnx | Weights | 91.0 MB | c623d0bcb99f |
| onnx/model_bnb4.onnx | Weights | 54.5 MB | 9e31a2ab7661 |
| onnx/model_fp16.onnx | Weights | 45.6 MB | a8b79f5c22bc |
| onnx/model_int8.onnx | Weights | 23.0 MB | a13ec391ca99 |
| onnx/model_q4.onnx | Weights | 55.2 MB | 3ad0785ed300 |
| onnx/model_q4f16.onnx | Weights | 30.3 MB | d860ca7adb70 |
| onnx/model_quantized.onnx | Weights | 23.1 MB | e9d8ebf845c4 |
| onnx/model_uint8.onnx | Weights | 23.0 MB | c259e88ff6fd |
| config.json | Configuration | 824 B | — |
| quantize_config.json | Configuration | 722 B | — |
| special_tokens_map.json | Configuration | 125 B | — |
| README.md | Documentation | 1.8 KB | — |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer.json | Tokenizer | 711.4 KB | — |
| tokenizer_config.json | Tokenizer | 1.2 KB | — |
| vocab.txt | Tokenizer | 231.5 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 345.8 MB
Download from Joshua
Released by Joshua through its official repository on Hugging Face.
Built From
- Derived from cross-encoder/ms-marco-MiniLM-L6-v2
- Quantized from cross-encoder/ms-marco-MiniLM-L6-v2
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 345.8 MB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About ms-marco-MiniLM-L-6-v2
What is ms-marco-MiniLM-L-6-v2's context length?
512 tokens, from the maximum position embeddings in its published configuration.
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