From c2d3fccba23c40ec59c87c5accb3e2a7f16bd5bf Mon Sep 17 00:00:00 2001
From: ishaansehgal99 <ishaanforthewin@gmail.com>
Date: Mon, 2 Oct 2023 19:05:42 -0700
Subject: [PATCH] nit: remove uncessary file

---
 presets/falcon/inference.py | 61 -------------------------------------
 1 file changed, 61 deletions(-)
 delete mode 100644 presets/falcon/inference.py

diff --git a/presets/falcon/inference.py b/presets/falcon/inference.py
deleted file mode 100644
index 3125f5b5b..000000000
--- a/presets/falcon/inference.py
+++ /dev/null
@@ -1,61 +0,0 @@
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import transformers
-import torch
-
-model_id = "tiiuae/falcon-7b"
-
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(
-    model_id,
-    device_map="auto",
-    torch_dtype=torch.bfloat16,
-    trust_remote_code=True,
-    # offload_folder="offload",
-    # offload_state_dict = True
-    # load_in_8bit=True, Uncomment for 8bit quantization
-)
-pipeline = transformers.pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-    torch_dtype=torch.bfloat16,
-    trust_remote_code=True,
-    device_map="auto",
-)
-sequences = pipeline(
-   "Girafatron is obsessed with giraffes, the most glorious animal on the face of this Earth. Giraftron believes all other animals are irrelevant when compared to the glorious majesty of the giraffe.\nDaniel: Hello, Girafatron!\nGirafatron:",
-    max_length=200,
-    do_sample=True,
-    top_k=10,
-    num_return_sequences=1,
-    eos_token_id=tokenizer.eos_token_id,
-)
-
-'''
-Without transformers.pipeline
-# Initialize the accelerator
-accelerator = Accelerator()
-print(accelerator.device)
-model, tokenizer = accelerator.prepare(model, tokenizer)
-
-input_text = "Girafatron is obsessed with giraffes, the most glorious animal on the face of this Earth. Giraftron believes all other animals are irrelevant when compared to the glorious majesty of the giraffe.\nDaniel: Hello, Girafatron!\nGirafatron:"
-
-# Tokenize the input_text
-input_ids = tokenizer.encode(input_text, return_tensors="pt")
-
-# Move input_ids to GPU
-input_ids = input_ids.to(accelerator.device)
-
-# Generate sequences
-sequences = model.generate(
-    input_ids=input_ids,
-    max_length=200,
-    do_sample=True,
-    top_k=10,
-    num_return_sequences=1,
-    eos_token_id=tokenizer.eos_token_id,
-)
-'''
-
-for seq in sequences:
-    print(f"Result: {seq['generated_text']}")