Inference
Without Sreaming
from unsloth.chat_templates import get_chat_template
tokenizer = get_chat_template(
tokenizer,
chat_template = "llama-3.1",
)
FastLanguageModel.for_inference(model) # Enable native 2x faster inference
messages = [
{"role": "user", "content": "What did the Prophet say about the importance of not wishing for death?"},
]
inputs = tokenizer.apply_chat_template(
messages,
tokenize = True,
add_generation_prompt = True, # Must add for generation
return_tensors = "pt",
).to("cuda")
outputs = model.generate(input_ids = inputs, max_new_tokens = 64, use_cache = True,
temperature = 1.5, min_p = 0.1)
tokenizer.batch_decode(outputs, skip_special_tokens=True)
With Streaming
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained(
model_name = "imranali291/sahi-ul-bukhari", # MODEL NAME HF MODEL REPO OR LOCAL PATH
max_seq_length = max_seq_length,
dtype = dtype,
load_in_4bit = load_in_4bit,
)
FastLanguageModel.for_inference(model) # Enable native 2x faster inference
messages = [
{"role": "user", "content": "What did the Prophet say about the importance of not wishing for death?"},
]
inputs = tokenizer.apply_chat_template(
messages,
tokenize = True,
add_generation_prompt = True, # Must add for generation
return_tensors = "pt",
).to("cuda")
from transformers import TextStreamer
text_streamer = TextStreamer(tokenizer, skip_prompt = True, skip_special_tokens=True)
_ = model.generate(input_ids = inputs, streamer = text_streamer, max_new_tokens = 128,
use_cache = True, temperature = 1.5, min_p = 0.1)
Sample questions
Question |
---|
What did the Prophet say about the importance of not wishing for death? |
What did the Prophet say about the importance of patience in afflictions? |
Who was Imam al-Bukhari? |
When was Imam al-Bukhari born? |
Inference Providers
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