Upload General Layer classifier

checkpoint.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d594e095e33799b5ac10602d95ee0924686ba944acc72c177caa57de06ff1054
+oid sha256:e7609a031219a1e4c32fd253c89a5bbe08132e5560740342edbc9f95e3193d5d
 size 1227506403

config.json

@@ -10,18 +10,18 @@
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
   "id2label": {
-    "0": "Cheer",
-    "1": "Game",
-    "2": "Broadcast",
-    "3": "Chat"
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3"
   },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "Broadcast": "2",
-    "Chat": "3",
-    "Cheer": "0",
-    "Game": "1"
+    "Broadcast": 2,
+    "Chat": 3,
+    "Cheer": 0,
+    "Game": 1
   },
   "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,

inference_example_1.py

@@ -1,17 +0,0 @@
-import torch
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-
-model = AutoModelForSequenceClassification.from_pretrained(
-    "scfengv/TVL_GeneralLayerClassifier",
-    id2label = {0: "Cheer", 1: "Game", 2: "Broadcast", 3: "Chat"},
-    label2id = {"Cheer": 0, "Game": 1, "Broadcast": 2, "Chat": 3}
-    )
-tokenizer = AutoTokenizer.from_pretrained("scfengv/TVL_GeneralLayerClassifier")
-
-inputs = tokenizer("中纖加油加油加油加油加油", return_tensors = "pt")
-
-with torch.no_grad():
-    logits = model(**inputs).logits
-
-predicted_class_id = logits.argmax().item()
-print(f"Predicted class: {predicted_class_id}")

inference_example_2.py

@@ -1,17 +0,0 @@
-import torch
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-
-model = AutoModelForSequenceClassification.from_pretrained(
-    "scfengv/TVL_GeneralLayerClassifier",
-    id2label = {0: "Cheer", 1: "Game", 2: "Broadcast", 3: "Chat"},
-    label2id = {"Cheer": 0, "Game": 1, "Broadcast": 2, "Chat": 3}
-    )
-tokenizer = AutoTokenizer.from_pretrained("scfengv/TVL_GeneralLayerClassifier")
-
-inputs = tokenizer("導播幽默~", return_tensors = "pt")
-
-with torch.no_grad():
-    logits = model(**inputs).logits
-
-predicted_class_id = logits.argmax().item()
-print(f"Predicted class: {predicted_class_id}")

inference_example_3.py

@@ -1,17 +0,0 @@
-import torch
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-
-model = AutoModelForSequenceClassification.from_pretrained(
-    "scfengv/TVL_GeneralLayerClassifier",
-    id2label = {0: "Cheer", 1: "Game", 2: "Broadcast", 3: "Chat"},
-    label2id = {"Cheer": 0, "Game": 1, "Broadcast": 2, "Chat": 3}
-    )
-tokenizer = AutoTokenizer.from_pretrained("scfengv/TVL_GeneralLayerClassifier")
-
-inputs = tokenizer("地震", return_tensors = "pt")
-
-with torch.no_grad():
-    logits = model(**inputs).logits
-
-predicted_class_id = logits.argmax().item()
-print(f"Predicted class: {predicted_class_id}")

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e0818306c441a11114cb1f44c394b306a053f852fa7bb6e8ed04f4a1227120b2
+oid sha256:6d7dae159b7de063195b05f2fc19a13d0e48aadf3d5cd8132feab71e57a27b90
 size 409110584

pytorch_model.bin

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7ea66227b4ab61d35cf3983c2aedc7f1479f26979222d744d5d7103b2d5e139c
-size 409156146