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---
datasets:
- WizardLM/WizardLM_evol_instruct_V2_196k
- Open-Orca/OpenOrca
language:
- en
---
# Writer/palmyra-20b-chat
---
# Usage
```py
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
from transformers import TextStreamer
model_name = "Writer/palmyra-20b-chat"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype=torch.float16,
device_map="auto",
)
prompt = "What is the meaning of life?"
input_text = (
"A chat between a curious user and an artificial intelligence assistant. "
"The assistant gives helpful, detailed, and polite answers to the user's questions. "
"USER: {prompt} "
"ASSISTANT:"
)
model_inputs = tokenizer(input_text.format(prompt=prompt), return_tensors="pt").to(
"cuda"
)
gen_conf = {
"top_k": 20,
"max_new_tokens": 2048,
"temperature": 0.6,
"do_sample": True,
"eos_token_id": tokenizer.eos_token_id,
}
streamer = TextStreamer(tokenizer)
if "token_type_ids" in model_inputs:
del model_inputs["token_type_ids"]
all_inputs = {**model_inputs, **gen_conf}
_ = model.generate(**all_inputs, streamer=streamer)
``` |