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--- |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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language: |
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- ta |
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tags: |
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- pretrained |
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inference: |
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parameters: |
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temperature: 0.7 |
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datasets: |
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- Hemanth-thunder/tamil-madlad-400 |
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--- |
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# Model Card for Tamil-Mistral-7B-v0.1 |
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The Tamil-Mistral-7B-v0.1 Large Language Model (LLM) is a pre-trained generative text model trained at the top of mistral base model 7 billion parameters. This is extends version of tokenization capability by increasing tamil tokens by 20k. |
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Additionally, it was Pretrained on 1.19 million Tamil documents sourced from madlad-400 (Tamil) [MADLAD-400 (Multilingual Audited Dataset: Low-resource And Document-level)](https://arxiv.org/abs/2309.04662). |
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pretraining time: 145 hours (GPU NVIDIA RTX A6000 48GB) |
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## Mistral model details |
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For full details of this model please read our [paper](https://arxiv.org/abs/2310.06825) and [release blog post](https://mistral.ai/news/announcing-mistral-7b/). |
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## Model Architecture |
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Mistral-7B-v0.1 is a transformer model, with the following architecture choices: |
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- Grouped-Query Attention |
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- Sliding-Window Attention |
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- Byte-fallback BPE tokenizer |
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#### Running the model on a GPU |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("Hemanth-thunder/Tamil-Mistral-7B-v0.1") |
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model = AutoModelForCausalLM.from_pretrained("Hemanth-thunder/Tamil-Mistral-7B-v0.1") |
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input_text = "ஒரு கிராமத்தில் பண்ணையார் ஒருவர் வாழ்ந்து வந்தார்." |
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input_ids = tokenizer(input_text, return_tensors="pt") |
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outputs = model.generate(**input_ids) |
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print(tokenizer.decode(outputs[0])) |
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``` |
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## Troubleshooting |
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- If you see the following error: |
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``` |
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KeyError: 'mistral' |
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``` |
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- Or: |
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``` |
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NotImplementedError: Cannot copy out of meta tensor; no data! |
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``` |
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Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer. |
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## Notice |
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Mistral 7B is a pretrained base model and therefore does not have any moderation mechanisms. |
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## The Mistral AI Team |
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Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed. |