serpdotai/sparsetral-16x7B-v1

Model

prompt format

1

6 commits

3 linked in READMEs

updated Jan 30, 2024

See the code

README

prompt format

### System:\n{system}\n### Human:\n{user}\n### Assistant:\n"

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("serpdotai/sparsetral-16x7B-v1", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("serpdotai/sparsetral-16x7B-v1", device_map="auto", trust_remote_code=True).eval()

inputs = tokenizer('### System:\n\n### Human:\nHow are you?\n### Assistant:\n', return_tensors='pt')
inputs = inputs.to(model.device)
pred = model.generate(**inputs)
print(tokenizer.decode(pred.cpu()[0], skip_special_tokens=True))
# I am doing well, thank you.
custom_code
endpoints_compatible
safetensors
sparsetral
text-generation
transformers

serpdotai/sparsetral-16x7B-v1

Model

prompt format

1

6 commits

3 linked in READMEs

updated Jan 30, 2024

See the code

README

prompt format

### System:\n{system}\n### Human:\n{user}\n### Assistant:\n"

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("serpdotai/sparsetral-16x7B-v1", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("serpdotai/sparsetral-16x7B-v1", device_map="auto", trust_remote_code=True).eval()

inputs = tokenizer('### System:\n\n### Human:\nHow are you?\n### Assistant:\n', return_tensors='pt')
inputs = inputs.to(model.device)
pred = model.generate(**inputs)
print(tokenizer.decode(pred.cpu()[0], skip_special_tokens=True))
# I am doing well, thank you.
custom_code
endpoints_compatible
safetensors
sparsetral
text-generation
transformers