catallama
/

CataLlama-v0.2-Base

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 ---
+license: llama3
+base_model: [meta-llama/Meta-Llama-3-8B-Instruct, catallama/CataLlama-v0.1-Base]
+tags:
+- llama
+- llama-3
+- Catalan
+model-index:
+- name: CataLlama-v0.2-Base
+  results: []
+datasets:
+- catallama/Catalan-Raw-Text
+language:
+- ca
+- en
+pipeline_tag: text-generation
 ---
 ## Model Details
+**CataLlama-v0.2-Base** is a merge between [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) and [catallama/CataLlama-v0.1-Base](https://huggingface.co/catallama/CataLlama-v0.1-Base)
+The resulting model retained the Catalan language skills of CataLlama-v0.1-Base, while acquiring basic skills in instruction following.
+**This is a base model and it is not fine-tuned for downstream tasks.** although it has acquired some instruction following skills after the merge.
+**Model developers** [Laurentiu Petrea](https://www.linkedin.com/in/laurentiupetrea/).
+**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)
+### Use with transformers
+See the snippet below for usage with Transformers:
+```python
+import transformers
+import torch
+model_id = "catallama/CataLlama-v0.2-Base"
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device_map="auto",
+)
+outputs = pipeline("Ei com estàs avui?")
+print(outputs[0]["generated_text"][len(prompt):])
+```
+## Merging procedure
+The merge was performed only 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 a 2/3 proportion of CataLlama-v0.1-Base and 1/3 proportion of Meta-Llama-3-8B-Instruct.
+The embedding, norm and head layers are copied from Meta-Llama-3-8B-Instruct 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.