This model is the 5th extracted standalone model from the
mistralai/Mixtral-8x7B-v0.1, using the
Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is experimental. It is expected to be worse than Mistral-7B.
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_name = "DrNicefellow/Mistral-5-from-Mixtral-8x7B-v0.1"
4tokenizer = AutoTokenizer.from_pretrained(model_name)
5model = AutoModelForCausalLM.from_pretrained(model_name)
6
7text = "Today is a pleasant"
8input_ids = tokenizer.encode(text, return_tensors='pt')
9output = model.generate(input_ids)
10
11print(tokenizer.decode(output[0], skip_special_tokens=True))
This model is available under the Apache 2.0 License.
This model is open-sourced under the Apache 2.0 License. See the LICENSE file for more details.