File size: 1,885 Bytes
243f824 3b7442b 243f824 2959013 243f824 2959013 243f824 adf9d95 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
datasets:
- WizardLM/WizardLM_evol_instruct_V2_196k
- Open-Orca/OpenOrca
language:
- en
tags:
- chat
- palmyra
---
# Writer/palmyra-20b-chat
---
# Usage
```py
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, 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}
output = model.generate(**all_inputs, streamer=streamer)
print("-"*20)
print(output)
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Writer__palmyra-20b-chat)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 38.97 |
| ARC (25-shot) | 43.52 |
| HellaSwag (10-shot) | 72.83 |
| MMLU (5-shot) | 35.18 |
| TruthfulQA (0-shot) | 43.17 |
| Winogrande (5-shot) | 66.46 |
| GSM8K (5-shot) | 3.94 |
| DROP (3-shot) | 7.7 |
|