Add model card

@Meg



@Ezi



If anyone has more resources on the training/evaluation of this model so we can flesh out those sections, that would be much appreciated!

README.md

@@ -1,10 +1,121 @@
 ---
+language: en
 tags:
 - exbert
 
 license: cc-by-nc-4.0
 ---
 
+# xlm-mlm-en-2048
+
+#  Table of Contents
+
+1. [Model Details](#model-details)
+2. [Uses](#uses)
+3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
+4. [Training](#training)
+5. [Evaluation](#evaluation)
+6. [Environmental Impact](#environmental-impact)
+7. [Citation](#citation)
+8. [Model Card Authors](#model-card-authors)
+9. [How To Get Started With the Model](#how-to-get-started-with-the-model)
+
+
+# Model Details
+
+The XLM model was proposed in [Cross-lingual Language Model Pretraining](https://arxiv.org/abs/1901.07291) by Guillaume Lample and Alexis Conneau. It’s a transformer pretrained with either a causal language modeling (CLM) objective (next token prediction), a masked language modeling (MLM) objective (BERT-like), or
+a Translation Language Modeling (TLM) object (extension of BERT’s MLM to multiple language inputs). This model is trained with a masked language modeling objective on English text. 
+
+## Model Description 
+
+- **Developed by:** Researchers affiliated with Facebook AI, see [associated paper](https://arxiv.org/abs/1901.07291) and [GitHub Repo](https://github.com/facebookresearch/XLM)
+- **Model type:** Language model
+- **Language(s) (NLP):** English
+- **License:** CC-BY-NC-4.0
+- **Related Models:** Other [XLM models](https://huggingface.co/models?sort=downloads&search=xlm)
+- **Resources for more information:** 
+  - [Cross-lingual Language Model Pretraining](https://arxiv.org/abs/1901.07291) by Guillaume Lample and Alexis Conneau (2019)
+  - [Unsupervised Cross-lingual Representation Learning at Scale](https://arxiv.org/pdf/1911.02116.pdf) by Conneau et al. (2020)
+  - [GitHub Repo](https://github.com/facebookresearch/XLM)
+  - [Hugging Face XLM docs](https://huggingface.co/docs/transformers/model_doc/xlm)
+
+# Uses
+
+## Direct Use
+
+The model is a language model. The model can be used for masked language modeling. 
+
+## Downstream Use
+
+To learn more about this task and potential downstream uses, see the Hugging Face [fill mask docs](https://huggingface.co/tasks/fill-mask) and the [Hugging Face Multilingual Models for Inference](https://huggingface.co/docs/transformers/v4.20.1/en/multilingual#xlm-with-language-embeddings) docs. Also see the [associated paper](https://arxiv.org/abs/1901.07291).
+
+## Out-of-Scope Use
+
+The model should not be used to intentionally create hostile or alienating environments for people. 
+
+# Bias, Risks, and Limitations
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
+
+## Recommendations
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
+
+# Training 
+
+More information needed. See the [associated GitHub Repo](https://github.com/facebookresearch/XLM).
+ 
+# Evaluation 
+
+More information needed. See the [associated GitHub Repo](https://github.com/facebookresearch/XLM).
+
+# Environmental Impact
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** More information needed
+- **Hours used:** More information needed
+- **Cloud Provider:** More information needed
+- **Compute Region:** More information needed
+- **Carbon Emitted:** More information needed
+
+# Citation 
+
+**BibTeX:**
+
+```bibtex
+@article{lample2019cross,
+  title={Cross-lingual language model pretraining},
+  author={Lample, Guillaume and Conneau, Alexis},
+  journal={arXiv preprint arXiv:1901.07291},
+  year={2019}
+}
+```
+
+**APA:**
+- Lample, G., & Conneau, A. (2019). Cross-lingual language model pretraining. arXiv preprint arXiv:1901.07291.
+
+# Model Card Authors 
+
+This model card was written by the team at Hugging Face.
+
+# How to Get Started with the Model
+
+Use the code below to get started with the model. See the [Hugging Face XLM docs](https://huggingface.co/docs/transformers/model_doc/xlm) for more examples.
+
+```python
+from transformers import XLMTokenizer, XLMModel
+import torch
+
+tokenizer = XLMTokenizer.from_pretrained("xlm-mlm-en-2048")
+model = XLMModel.from_pretrained("xlm-mlm-en-2048")
+
+inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
+outputs = model(**inputs)
+
+last_hidden_states = outputs.last_hidden_state
+```
+
 <a href="https://huggingface.co/exbert/?model=xlm-mlm-en-2048">
 	<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
 </a>