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neody/riva-translate-4b-instruct-gptq-int8
riva-translate-4b-instruct-gptq-int8 is a machine learning model from neody. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
Quantized using gptq with random articles sampled from finewiki
Downloads · 30 days
12
12% of all-time downloads
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From the Hugging Face model README
Quantized using gptq with random articles sampled from finewiki
Somehow broken, use neody/riva-translate-4b-instruct-gptq-int8-w64
The Riva-Translate-4B-Instruct Neural Machine Translation model translates text in 12 languages. The supported languages are: English(en), German(de), European Spanish(es-ES), LATAM Spanish(es-US), France(fr), Brazillian Portugese(pt-BR), Russian(ru), Simplified Chinese(zh-CN), Traditional Chinese(zh-TW), Japanese(ja),Korean(ko), Arabic(ar). This model was developed based on the decoder-only Transformer architecture. It is a fine-tuned version of a 4B Base model that was pruned and distilled from nvidia/Mistral-NeMo-Minitron-8B-Base using our LLM compression technique. The model was trained using a multi-stage CPT and SFT. It uses tiktoken as the tokenizer. The model supports a context length of 8K tokens.
Model Developer: NVIDIA
Model Dates: Riva-Translate-4B-Instruct was trained between Jan 2025 and April 2025.
NVIDIA Open Model License Agreement
For documentation, deployment guides, enterprise-ready APIs, and the latest open models—including Nemotron and other cutting-edge speech, translation, and generative AI—visit the NVIDIA Developer Portal at developer.nvidia.com. Join the community to access tools, support, and resources to accelerate your development with NVIDIA’s NeMo, Riva, NIM, and foundation models.<br>
What is Nemotron?<br> NVIDIA Developer Nemotron<br> NVIDIA Riva Speech<br> NeMo Documentation<br>
We recommend using the following prompt template, which was used to fine-tune the model. The model may not perform optimally without it.
<s>System
{system prompt}</s>
<s>User
{user prompt}</s>
<s>Assistant\n
<s>Assistant as a generation prompt.For example, to translate an English sentence into Simplified Chinese:
<s>System
You are an expert at translating text from English to Simplified Chinese.</s>
<s>User
What is the Simplified Chinese translation of the sentence: The GRACE mission is a collaboration between the NASA and German Aerospace Center.?</s>
<s>Assistant
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("nvidia/Riva-Translate-4B-Instruct")
model = AutoModelForCausalLM.from_pretrained("nvidia/Riva-Translate-4B-Instruct").cuda()
# Use the prompt template
messages = [
{
"role": "system",
"content": "You are an expert at translating text from English to Simplified Chinese.",
},
{"role": "user", "content": "What is the Simplified Chinese translation of the sentence: The GRACE mission is a collaboration between the NASA and German Aerospace Center.?"},
]
tokenized_chat = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(model.device)
outputs = model.generate(tokenized_chat, max_new_tokens=128, pad_token_id=tokenizer.eos_token_id)
print(tokenizer.decode(outputs[0]))
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
Accuracy varies based on the characteristics of input (Domain, Use Case, Noise, Context, etc.). Grammar errors and semantic issues may be present. As a potential mitigation, the user can change the prompt to get a better translation.
Abide by NVIDIA Open Model License Agreement