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Model: AI-Sweden-Models/gpt-sw3-6.7b-v2-translator
Source: Original Platform

README.md

@@ -0,0 +1,80 @@
+---
+base_model: AI-Sweden-Models/gpt-sw3-6.7b-v2-instruct
+language:
+- sv
+- da
+- 'no'
+- en
+pipeline_tag: text-generation
+inference:
+  parameters:
+    temperature: 0.7
+tags:
+- translation
+---
+# Model Card for gpt-sw3-6.7b-v2-translator
+The `gpt-sw3-6.7b-v2-translator` is a finetuned version of `gpt-sw3-6.7b-v2-instruct` on a carefully selected translation pair dataset that was gathered by AI Sweden.
+
+
+## Intended usage:
+Translate text data from English to Swedish, or Swedish to English.
+
+
+## How to use:
+```python
+import torch
+from transformers import pipeline, StoppingCriteriaList, StoppingCriteria
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+
+# (Optional) - define a stopping criteria
+# We ideally want the model to stop generate once the response from the Bot is generated
+class StopOnTokenCriteria(StoppingCriteria):
+    def __init__(self, stop_token_id):
+        self.stop_token_id = stop_token_id
+
+    def __call__(self, input_ids, scores, **kwargs):
+        return input_ids[0, -1] == self.stop_token_id
+
+
+pipe = pipeline(
+    task="text-generation",
+    model="AI-Sweden-Models/gpt-sw3-6.7b-v2-translator",
+    device=device
+)
+
+stop_on_token_criteria = StopOnTokenCriteria(stop_token_id=pipe.tokenizer.bos_token_id)
+text = "I like to eat ice cream in the summer."
+
+# This will translate English to Swedish
+# To translate from Swedish to English the prompt would be:
+# prompt = f"<|endoftext|><s>User: Översätt till Engelska från Svenska\n{text}<s>Bot:"
+
+prompt = f"<|endoftext|><s>User: Översätt till Svenska från Engelska\n{text}<s>Bot:"
+
+input_tokens = pipe.tokenizer(prompt, return_tensors="pt").input_ids.to(device)
+max_model_length = 2048
+dynamic_max_length = max_model_length - input_tokens.shape[1]
+
+response = pipe(
+    prompt,
+    max_length=dynamic_max_length,
+    truncation=True,
+    stopping_criteria=StoppingCriteriaList([stop_on_token_criteria])
+)
+
+print(response[0]["generated_text"].split("<s>Bot: ")[-1])
+```
+```python
+>>> "Jag tycker om att äta glass på sommaren."
+```
+
+## Training & Data:
+The training was done on 1 NVIDIA DGX using DeepSpeed ZeRO 3 for three epochs on roughly 4GB of carefully selected translation data. It is a full finetune of all of the model parameters. 
+
+| Epoch | Training Loss | Evaluation Loss |
+|-------|---------------|-----------------|
+| 1     | 1.309         | 1.281           |
+| 2     | 1.161         | 1.242           |
+| 3     | 1.053         | 1.219           |