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--- |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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tags: |
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- finetuned |
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--- |
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# ExLLaMA v2 quantization of Mistral-7B-Instruct-v0.1 |
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Use [text-generation-webui](https://github.com/oobabooga/text-generation-webui) or [exllamav2](https://github.com/turboderp/exllamav2) |
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# Model Card for Mistral-7B-Instruct-v0.1 |
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The Mistral-7B-Instruct-v0.1 Large Language Model (LLM) is a instruct fine-tuned version of the [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) generative text model using a variety of publicly available conversation datasets. |
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For full details of this model please read our [release blog post](https://mistral.ai/news/announcing-mistral-7b/) |
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## Instruction format |
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In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[\INST]` tokens. The very first instruction should begin with a begin of sentence id. The next instructions should not. The assistant generation will be ended by the end-of-sentence token id. |
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E.g. |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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device = "cuda" # the device to load the model onto |
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model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") |
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tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") |
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text = "<s>[INST] What is your favourite condiment? [/INST]" |
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"Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!</s> " |
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"[INST] Do you have mayonnaise recipes? [/INST]" |
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encodeds = tokenizer(instructions, return_tensors="pt", add_special_tokens=False) |
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model_inputs = encodeds.to(device) |
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model.to(device) |
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generated_ids = model.generate(**model_inputs, max_new_tokens=1000, do_sample=True) |
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decoded = tokenizer.batch_decode(generated_ids) |
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print(decoded[0]) |
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``` |
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## Model Architecture |
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This instruction model is based on Mistral-7B-v0.1, 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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## 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. |
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