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'
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, Lélio Renard Lavaud, Louis Ternon, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.
Runs of MaziyarPanahi Mistral-7B-Instruct-v0.2 on huggingface.co
1.7K
Total runs
20
24-hour runs
-249
3-day runs
-494
7-day runs
131
30-day runs
More Information About Mistral-7B-Instruct-v0.2 huggingface.co Model
Mistral-7B-Instruct-v0.2 huggingface.co is an AI model on huggingface.co that provides Mistral-7B-Instruct-v0.2's model effect (), which can be used instantly with this MaziyarPanahi Mistral-7B-Instruct-v0.2 model. huggingface.co supports a free trial of the Mistral-7B-Instruct-v0.2 model, and also provides paid use of the Mistral-7B-Instruct-v0.2. Support call Mistral-7B-Instruct-v0.2 model through api, including Node.js, Python, http.
Mistral-7B-Instruct-v0.2 huggingface.co is an online trial and call api platform, which integrates Mistral-7B-Instruct-v0.2's modeling effects, including api services, and provides a free online trial of Mistral-7B-Instruct-v0.2, you can try Mistral-7B-Instruct-v0.2 online for free by clicking the link below.
MaziyarPanahi Mistral-7B-Instruct-v0.2 online free url in huggingface.co:
Mistral-7B-Instruct-v0.2 is an open source model from GitHub that offers a free installation service, and any user can find Mistral-7B-Instruct-v0.2 on GitHub to install. At the same time, huggingface.co provides the effect of Mistral-7B-Instruct-v0.2 install, users can directly use Mistral-7B-Instruct-v0.2 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
Mistral-7B-Instruct-v0.2 install url in huggingface.co: