catallama
/

CataLlama-v0.2-Instruct-SFT-DPO-Merged

@@ -1,201 +1,113 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-GSM8K: 77.26
-MMLU: 60.53
-## Model Details
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 ---
+license: llama3
+base_model:
+- catallama/CataLlama-v0.2-Instruct-SFT
+- catallama/CataLlama-v0.2-Instruct-DPO
+tags:
+- llama
+- llama-3
+- catalan
+model-index:
+- name: CataLlama-v0.2-Instruct-SFT-DPO-Merged
+  results: []
+datasets:
+- catallama/Catalan-DPO-V2
+- catallama/Catalan-Instruct-V2
+language:
+- ca
+- en
+pipeline_tag: text-generation
 ---
+![](https://huggingface.co/catallama/CataLlama-v0.2-Instruct-SFT/resolve/main/CataLlama-v0.2.png)
+# CataLlama-v0.2-Instruct-SFT-DPO-Merged
+**CataLlama-v0.2-Instruct-SFT-DPO-Merged** is a merge between [catallama/CataLlama-v0.2-Instruct-SFT](https://huggingface.co/catallama/CataLlama-v0.2-Instruct-SFT) and [catallama/CataLlama-v0.2-Instruct-DPO](https://huggingface.co/catallama/CataLlama-v0.2-Instruct-DPO)
+The resulting model scores better than it's parents on both MMLU and GSM8K.
+**This is an instruction fine-tuned model, optimised with DPO, proficient on the following tasks in Catalan**
+- *Information extraction (suitable for RAG)*
+- *Named Entity Recognition (NER)*
+- *Translation from English to Catalan and Catalan to English*
+- *Summarization - both short form and long form*
+- *Sentiment analysis*
+- *Chat*
+**Model developers** [Laurentiu Petrea](https://www.linkedin.com/in/laurentiupetrea/) based on Llama-3 from Meta.
+**Model Architecture** CataLlama is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and direct preference optimisation (DPO) to align with human preferences for helpfulness and safety.
+**License** The model uses the llama-3 license available at: [https://llama.meta.com/llama3/license](https://llama.meta.com/llama3/license)
+## Benchmarks
+| Model              | CataLlama-v0.2-Instruct-DPO | CataLlama-v0.2-Instruct-SFT     | CataLlama-v0.2-Instruct-SFT-DPO-Merged     |
+| ------------------ | --------------------------- | ------------------------------- | ------------------------------------------ |
+| MMLU 5 shot        | 58.89                       | 59.35                           | **60.53**                                  |
+| GSM8K CoT 8 shot   | 60.05                       | 76.04                           | **77.26**                                  |
+### Use with transformers
+See the snippet below for usage with Transformers:
+**The model follows the same prompt template as Llama-3 Instruct**
+```python
+import transformers
+import torch
+model_id = "catallama/CataLlama-v0.2-Instruct-SFT-DPO-Merged"
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device_map="auto",
+)
+messages = [
+    {"role": "user", "content": "Ei com estàs avui?"},
+]
+prompt = pipeline.tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+outputs = pipeline(
+    prompt,
+    max_new_tokens=1024,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+print(outputs[0]["generated_text"][len(prompt):])
+```
+## Merging procedure
+The merge was performed between the 32 layers of the two models, excluding the embedding, norm and the head layers.
+The weights of the 32 layers were merged in equal proportion simply by calculating the average of the corresponding weights from the parent models.
+The embedding, norm and head layers are copied from CataLlama-v0.2-Instruct-DPO without modification.
+**This was done with a custom script, without mergekit.**
+## Intended Use
+**Note:** This model is not intended to beat benchmarks, but to demonstrate techniques for augmenting LLMs on new languages and preserve rare languages as part of our world heritage.
+**Intended Use Cases** Llama 3 is intended for commercial and research use in English. Instruction tuned models are intended for assistant-like chat, whereas pretrained models can be adapted for a variety of natural language generation tasks.
+**Out-of-scope** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3 Community License. Use in languages other than English**.
+**Note: Developers may fine-tune Llama 3 models for languages beyond English provided they comply with the Llama 3 Community License and the Acceptable Use Policy.