54 lines
2.3 KiB
Markdown
54 lines
2.3 KiB
Markdown
---
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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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# Sharded version of Mistral-7B-Instruct-v0.1
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This is the sharded version of Mistral-7B-Instruct-v0.1 so you can use it when you have limited CPU memory
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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(text, 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. |