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README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- ab3223323/esgBERTv1_Access_to_Finance
+- ab3223323/esgBERTv1_Access_to_Communications
+base_model:
+- ab3223323/esgBERTv1_Access_to_Finance
+- ab3223323/esgBERTv1_Access_to_Communications
+---
+
+# test
+
+test is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [ab3223323/esgBERTv1_Access_to_Finance](https://huggingface.co/ab3223323/esgBERTv1_Access_to_Finance)
+* [ab3223323/esgBERTv1_Access_to_Communications](https://huggingface.co/ab3223323/esgBERTv1_Access_to_Communications)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: ab3223323/esgBERTv1_Access_to_Finance
+        layer_range: [0, 12]
+      - model: ab3223323/esgBERTv1_Access_to_Communications
+        layer_range: [0, 12]
+merge_method: slerp
+base_model: ab3223323/esgBERTv1_Access_to_Finance
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "ab3223323/test"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```

config.json

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+{
+  "_name_or_path": "ab3223323/esgBERTv1_Access_to_Finance",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Access to Finance",
+    "1": "Other"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Access to Finance": 0,
+    "Other": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.40.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

mergekit_config.yml

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+
+slices:
+  - sources:
+      - model: ab3223323/esgBERTv1_Access_to_Finance
+        layer_range: [0, 12]
+      - model: ab3223323/esgBERTv1_Access_to_Communications
+        layer_range: [0, 12]
+merge_method: slerp
+base_model: ab3223323/esgBERTv1_Access_to_Finance
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+dtype: bfloat16

model-00001-of-00001.safetensors

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model.safetensors.index.json

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+      "rstrip": false,
+      "single_word": false,
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+    },
+    "103": {
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "max_length": 512,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}