https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2

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[wrLf5yaGC6]
mistralai
/
Mistral-7B-Instruct-v0.2
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Text Generation Transformers PyTorch Safetensors mistral finetuned 
conversational Inference Endpoints text-generation-inference
arxiv: 2310.06825
License: apache-2.0
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  * Model Card for Mistral-7B-Instruct-v0.2
      + Instruction format
      + Troubleshooting
      + Limitations
      + The Mistral AI Team

 Model Card for Mistral-7B-Instruct-v0.2

The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an
instruct fine-tuned version of the Mistral-7B-v0.2.

Mistral-7B-v0.2 has the following changes compared to Mistral-7B-v0.1

  * 32k context window (vs 8k context in v0.1)
  * Rope-theta = 1e6
  * No Sliding-Window Attention

For full details of this model please read our paper and release blog
post.

 Instruction format

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.

E.g.

text = "<s>[INST] What is your favourite condiment? [/INST]"
"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> "
"[INST] Do you have mayonnaise recipes? [/INST]"

This format is available as a chat template via the
apply_chat_template() method:

from transformers import AutoModelForCausalLM, AutoTokenizer

device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")

messages = [
    {"role": "user", "content": "What is your favourite condiment?"},
    {"role": "assistant", "content": "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!"},
    {"role": "user", "content": "Do you have mayonnaise recipes?"}
]

encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")

model_inputs = encodeds.to(device)
model.to(device)

generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])

 Troubleshooting

  * If you see the following error:

Traceback (most recent call last):
File "", line 1, in
File "/transformers/models/auto/auto_factory.py", line 482, in from_pretrained
config, kwargs = AutoConfig.from_pretrained(
File "/transformers/models/auto/configuration_auto.py", line 1022, in from_pretrained
config_class = CONFIG_MAPPING[config_dict["model_type"]]
File "/transformers/models/auto/configuration_auto.py", line 723, in getitem
raise KeyError(key)
KeyError: 'mistral'

Installing transformers from source should solve the issue pip
install git+https://github.com/huggingface/transformers

This should not be required after transformers-v4.33.4.

 Limitations

The Mistral 7B Instruct model is a quick demonstration that the base
model can be easily fine-tuned to achieve compelling performance. It
does not have any moderation mechanisms. We're looking forward to
engaging with the community on ways to make the model finely respect
guardrails, allowing for deployment in environments requiring
moderated outputs.

 The Mistral AI Team

Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Blanche Savary,
Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou
Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume
Lample, Lelio Renard Lavaud, Louis Ternon, Lucile Saulnier,
Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Theophile Gervet,
Thibaut Lavril, Thomas Wang, Timothee Lacroix, William El Sayed.

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