Improve language tag (#3)

- Improve language tag (01714fc8d10f2f838b67a6263921b089d6da502b)


Co-authored-by: Loïck BOURDOIS <[email protected]>

README.md

@@ -1,336 +1,342 @@
----
-language:
-- en
-license: apache-2.0
-library_name: transformers
-tags:
-- mergekit
-- merge
-- lazymergekit
-base_model:
-- Qwen/Qwen2.5-32B-Instruct
-license_name: tongyi-qianwen
-license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
-pipeline_tag: text-generation
-model-index:
-- name: BigQwen2.5-Echo-47B-Instruct
-  results:
-  - task:
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: IFEval (0-Shot)
-      type: HuggingFaceH4/ifeval
-      args:
-        num_few_shot: 0
-    metrics:
-    - type: inst_level_strict_acc and prompt_level_strict_acc
-      value: 73.57
-      name: strict accuracy
-    source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
-      name: Open LLM Leaderboard
-  - task:
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: BBH (3-Shot)
-      type: BBH
-      args:
-        num_few_shot: 3
-    metrics:
-    - type: acc_norm
-      value: 44.52
-      name: normalized accuracy
-    source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
-      name: Open LLM Leaderboard
-  - task:
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: MATH Lvl 5 (4-Shot)
-      type: hendrycks/competition_math
-      args:
-        num_few_shot: 4
-    metrics:
-    - type: exact_match
-      value: 3.47
-      name: exact match
-    source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
-      name: Open LLM Leaderboard
-  - task:
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: GPQA (0-shot)
-      type: Idavidrein/gpqa
-      args:
-        num_few_shot: 0
-    metrics:
-    - type: acc_norm
-      value: 8.61
-      name: acc_norm
-    source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
-      name: Open LLM Leaderboard
-  - task:
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: MuSR (0-shot)
-      type: TAUR-Lab/MuSR
-      args:
-        num_few_shot: 0
-    metrics:
-    - type: acc_norm
-      value: 10.19
-      name: acc_norm
-    source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
-      name: Open LLM Leaderboard
-  - task:
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: MMLU-PRO (5-shot)
-      type: TIGER-Lab/MMLU-Pro
-      config: main
-      split: test
-      args:
-        num_few_shot: 5
-    metrics:
-    - type: acc
-      value: 41.49
-      name: accuracy
-    source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
-      name: Open LLM Leaderboard
----
-
-# BigQwen2.5-Echo-47B-Instruct
-
-![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/98GiKtmH1AtHHbIbOUH4Y.jpeg)
-
-BigQwen2.5-Echo-47B-Instruct is a [Qwen/Qwen2-32B-Instruct](https://huggingface.co/Qwen/Qwen2-72B-Instruct) self-merge made with [MergeKit](https://github.com/arcee-ai/mergekit/tree/main).
-
-## 🔉 Echo Merge
-
-I've tried a more gradual approach with a **distributed repetition pattern**. Instead of replicating blocks of 8 or more layers, I'm replicating individual layers in these blocks:
-- First 8 layers: No replication
-- Next 8 layers: Replicate 2 layers (first one, middle one)
-- Next 8 layers: Replicate 4 layers (1st, 3rd, 5th, 7th)
-- Next 8 layers: Replicate 8 layers (all of them)
-- Next 8 layers: Replicate 4 layers (1st, 3rd, 5th, 7th)
-- Next 8 layers: Replicate 2 layers (first one, middle one)
-- First 8 layers: No replication
-
-I used this string to visualize it, where 0 are original layers and 1 duplicated ones (the order doesn't matter):
-```
-00000000 1000010000 100100100100 1010101010101010 1010101010101010 100100100100 1000010000 00000000 
-```
-
-The main idea is that the input/output difference of middle layers is quite small, so replicating a middle layer has a small impact on the output. 
-The additional layers are designed to increase the model's capacity without breaking the information flow, which often creates "insane" self-merges.
-
-## 🏆 Evaluation
-
-|      Metric       |**BigQwen2.5-Echo-47B-Instruct**|BigQwen2.5-52B-Instruct|Qwen2.5-32B-Instruct|
-|-------------------|----:|----:|----:|
-|Avg.               |30.31|37.42|36.17|
-|IFEval (0-Shot)    |73.57|79.29|83.46|
-|BBH (3-Shot)       |44.52|59.81|56.49|
-|MATH Lvl 5 (4-Shot)| 3.47|17.82|0|
-|GPQA (0-shot)      | 8.61| 6.94|11.74|
-|MuSR (0-shot)      |10.19|10.45|13.5|
-|MMLU-PRO (5-shot)  |41.49|50.22|51.85|
-
-## 🧩 Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-slices:
-  # First 8 layers: No replication
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [0, 8]
-
-  # Next 8 layers: Replicate 2 layers
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [8, 9]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [8, 9]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [9, 13]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [13, 14]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [13, 14]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [14, 16]
-
-  # Next 8 layers: Replicate 4 layers
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [16, 18]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [17, 19]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [18, 20]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [19, 21]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [20, 22]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [21, 23]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [22, 24]
-
-  # Next 8 layers: Replicate all 8 layers
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [24, 25]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [24, 26]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [25, 27]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [26, 28]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [27, 29]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [28, 30]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [29, 31]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [30, 32]
-
-  # Middle 8 layers: Replicate all 8 layers
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [32, 33]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [32, 34]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [33, 35]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [34, 36]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [35, 37]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [36, 38]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [37, 39]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [38, 40]
-
-  # Next 8 layers: Replicate 4 layers
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [40, 42]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [41, 43]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [42, 44]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [43, 45]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [44, 46]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [45, 47]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [46, 48]
-
-  # Next 8 layers: Replicate 2 layers
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [48, 49]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [48, 49]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [49, 53]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [53, 54]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [53, 54]
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [54, 56]
-
-  # Last 8 layers: No replication
-  - sources:
-    - model: Qwen/Qwen2.5-32B-Instruct
-      layer_range: [56, 64]
-
-merge_method: passthrough
-dtype: bfloat16
-```
-
-## 💻 Usage
-
-```python
-!pip install -qU transformers accelerate
-
-from transformers import AutoTokenizer
-import transformers
-import torch
-
-model = "mlabonne/BigQwen2.5-Echo-47B-Instruct"
-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"])
+---
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+license: apache-2.0
+library_name: transformers
+tags:
+- mergekit
+- merge
+- lazymergekit
+base_model:
+- Qwen/Qwen2.5-32B-Instruct
+license_name: tongyi-qianwen
+license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
+pipeline_tag: text-generation
+model-index:
+- name: BigQwen2.5-Echo-47B-Instruct
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 73.57
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 44.52
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 3.47
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 8.61
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 10.19
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 41.49
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=mlabonne/BigQwen2.5-Echo-47B-Instruct
+      name: Open LLM Leaderboard
+---
+
+# BigQwen2.5-Echo-47B-Instruct
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/98GiKtmH1AtHHbIbOUH4Y.jpeg)
+
+BigQwen2.5-Echo-47B-Instruct is a [Qwen/Qwen2-32B-Instruct](https://huggingface.co/Qwen/Qwen2-72B-Instruct) self-merge made with [MergeKit](https://github.com/arcee-ai/mergekit/tree/main).
+
+## 🔉 Echo Merge
+
+I've tried a more gradual approach with a **distributed repetition pattern**. Instead of replicating blocks of 8 or more layers, I'm replicating individual layers in these blocks:
+- First 8 layers: No replication
+- Next 8 layers: Replicate 2 layers (first one, middle one)
+- Next 8 layers: Replicate 4 layers (1st, 3rd, 5th, 7th)
+- Next 8 layers: Replicate 8 layers (all of them)
+- Next 8 layers: Replicate 4 layers (1st, 3rd, 5th, 7th)
+- Next 8 layers: Replicate 2 layers (first one, middle one)
+- First 8 layers: No replication
+
+I used this string to visualize it, where 0 are original layers and 1 duplicated ones (the order doesn't matter):
+```
+00000000 1000010000 100100100100 1010101010101010 1010101010101010 100100100100 1000010000 00000000 
+```
+
+The main idea is that the input/output difference of middle layers is quite small, so replicating a middle layer has a small impact on the output. 
+The additional layers are designed to increase the model's capacity without breaking the information flow, which often creates "insane" self-merges.
+
+## 🏆 Evaluation
+
+|      Metric       |**BigQwen2.5-Echo-47B-Instruct**|BigQwen2.5-52B-Instruct|Qwen2.5-32B-Instruct|
+|-------------------|----:|----:|----:|
+|Avg.               |30.31|37.42|36.17|
+|IFEval (0-Shot)    |73.57|79.29|83.46|
+|BBH (3-Shot)       |44.52|59.81|56.49|
+|MATH Lvl 5 (4-Shot)| 3.47|17.82|0|
+|GPQA (0-shot)      | 8.61| 6.94|11.74|
+|MuSR (0-shot)      |10.19|10.45|13.5|
+|MMLU-PRO (5-shot)  |41.49|50.22|51.85|
+
+## 🧩 Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+slices:
+  # First 8 layers: No replication
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [0, 8]
+
+  # Next 8 layers: Replicate 2 layers
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [8, 9]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [8, 9]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [9, 13]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [13, 14]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [13, 14]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [14, 16]
+
+  # Next 8 layers: Replicate 4 layers
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [16, 18]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [17, 19]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [18, 20]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [19, 21]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [20, 22]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [21, 23]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [22, 24]
+
+  # Next 8 layers: Replicate all 8 layers
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [24, 25]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [24, 26]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [25, 27]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [26, 28]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [27, 29]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [28, 30]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [29, 31]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [30, 32]
+
+  # Middle 8 layers: Replicate all 8 layers
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [32, 33]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [32, 34]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [33, 35]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [34, 36]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [35, 37]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [36, 38]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [37, 39]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [38, 40]
+
+  # Next 8 layers: Replicate 4 layers
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [40, 42]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [41, 43]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [42, 44]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [43, 45]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [44, 46]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [45, 47]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [46, 48]
+
+  # Next 8 layers: Replicate 2 layers
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [48, 49]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [48, 49]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [49, 53]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [53, 54]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [53, 54]
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [54, 56]
+
+  # Last 8 layers: No replication
+  - sources:
+    - model: Qwen/Qwen2.5-32B-Instruct
+      layer_range: [56, 64]
+
+merge_method: passthrough
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "mlabonne/BigQwen2.5-Echo-47B-Instruct"
+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"])
 ```