Update README.md

README.md

@@ -1,6 +1,9 @@
 ---
 library_name: transformers
-tags: []
+language:
+- en
+base_model:
+- sentence-transformers/all-MiniLM-L6-v2
 ---
 
 # Model Card for Model ID
@@ -18,12 +21,10 @@ tags: []
 This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
 - **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
 - **Model type:** [More Information Needed]
 - **Language(s) (NLP):** [More Information Needed]
 - **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Finetuned from model [optional]:** sentence-transformers/all-MiniLM-L6-v2
 
 ### Model Sources [optional]
 
@@ -49,18 +50,6 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 
 [More Information Needed]
 
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
 ### Recommendations
 
 <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
@@ -71,6 +60,19 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 Use the code below to get started with the model.
 
+```python
+from transformers import AutoModel, AutoTokenizer
+model_name = "sentence-transformers/all-MiniLM-L6-v2"
+
+# Load the tokenizer,model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModel.from_pretrained(model_name)
+model.load_adapter("esg-x/esg-embedding-model")
+
+text = "I love ESG"
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model(**inputs)
+```
 [More Information Needed]
 
 ## Training Details
@@ -138,62 +140,9 @@ Use the code below to get started with the model.
 
 [More Information Needed]
 
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-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]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
 
 ## Glossary [optional]
 
 <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
 
 [More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
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-[More Information Needed]
-
-## Model Card Contact
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-[More Information Needed]