Dolphin Mistral Instruct
This is a custom language model created using the "SLERP" method
Models based on
The following models were used to create this language model:
Configuration
The following configuration was used to produce this model:
base_model:
- arcee-ai/sec-mistral-7b-instruct-1.6-epoch
- cognitivecomputations/dolphin-2.8-mistral-7b-v02
library_name: transformers
dtype: bfloat16
Usage
This model uses SafeTensors files and can be loaded and used with the Transformers library. Here's an example of how to load and generate text with the model using Transformers and Python:
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "path/to/model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
input_text = "Write a short story about"
input_ids = tokenizer.encode(input_text, return_tensors="pt").to(model.device)
output_ids = model.generate(
input_ids,
max_length=200,
do_sample=True,
top_k=50,
top_p=0.95,
num_return_sequences=1,
)
output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
print(output_text)
Make sure to replace "path/to/model" with the actual path to your model's directory.
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Model tree for grandell1234/dolphin-mistral-instruct-7b
Base model
arcee-ai/sec-mistral-7b-instruct-1.6-epoch