Update README.md

README.md

@@ -1,20 +1,25 @@
 ---
 tags:
-- generated_from_trainer
+  - bittensor
+  - subnet-20
+  - agent
+  - function-calling
+  - generated_from_trainer
 license: mit
 datasets:
-- HuggingFaceH4/ultrachat_200k
-- HuggingFaceH4/ultrafeedback_binarized
+  - HuggingFaceH4/ultrachat_200k
+  - HuggingFaceH4/ultrafeedback_binarized
 language:
-- en
+  - en
 base_model: mistralai/Mistral-7B-v0.1
+pipeline_tag: text-generation
 widget:
   - example_title: Pirate!
     messages:
       - role: system
         content: You are a pirate chatbot who always responds with Arr!
       - role: user
-        content: "There's a llama on my lawn, how can I get rid of him?"
+        content: There's a llama on my lawn, how can I get rid of him?
     output:
       text: >-
         Arr! 'Tis a puzzlin' matter, me hearty! A llama on yer lawn be a rare
@@ -23,422 +28,143 @@ widget:
         promise of a tasty treat. Once he's gone, ye can clean up yer lawn and
         enjoy the peace and quiet once again. But beware, me hearty, for there
         may be more llamas where that one came from! Arr!
-pipeline_tag: text-generation
 model-index:
-- name: zephyr-7b-beta
-  results:
-  # AI2 Reasoning Challenge (25-Shot)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: AI2 Reasoning Challenge (25-Shot)
-      type: ai2_arc
-      config: ARC-Challenge
-      split: test
-      args:
-        num_few_shot: 25
-    metrics:
-       - type: acc_norm
-         name: normalized accuracy
-         value: 62.03071672354948
-    source:
-      name: Open LLM Leaderboard
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta
-
-  # HellaSwag (10-shot)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: HellaSwag (10-Shot)
-      type: hellaswag
-      split: validation
-      args:
-        num_few_shot: 10
-    metrics:
-       - type: acc_norm
-         name: normalized accuracy
-         value: 84.35570603465445
-    source:
-      name: Open LLM Leaderboard
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta
-
-  # DROP (3-shot)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: Drop (3-Shot)
-      type: drop
-      split: validation
-      args:
-        num_few_shot: 3
-    metrics:
-       - type: f1
-         name: f1 score
-         value: 9.662437080536909
-    source:
-      name: Open LLM Leaderboard
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta
-
-  # TruthfulQA (0-shot)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: TruthfulQA (0-shot)
-      type: truthful_qa
-      config: multiple_choice
-      split: validation
-      args:
-        num_few_shot: 0
-    metrics:
-       - type: mc2
-         value: 57.44916942762855
-    source:
-      name: Open LLM Leaderboard
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta
-
-  # GSM8k (5-shot)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: GSM8k (5-shot)
-      type: gsm8k
-      config: main
-      split: test
-      args:
-        num_few_shot: 5
-    metrics:
-       - type: acc
-         name: accuracy
-         value: 12.736921910538287
-    source:
-      name: Open LLM Leaderboard
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta
-
-  # MMLU (5-Shot)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: MMLU (5-Shot)
-      type: cais/mmlu
-      config: all
-      split: test
-      args:
-        num_few_shot: 5
-    metrics:
-       - type: acc
-         name: accuracy
-         value: 61.07
-    source:
-      name: Open LLM Leaderboard
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta
-
-  # Winogrande (5-shot)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: Winogrande (5-shot)
-      type: winogrande
-      config: winogrande_xl
-      split: validation
-      args:
-        num_few_shot: 5
-    metrics:
-       - type: acc
-         name: accuracy
-         value: 77.74269928966061
-    source:
-      name: Open LLM Leaderboard
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta
-
-  # AlpacaEval (taken from model card)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: AlpacaEval
-      type: tatsu-lab/alpaca_eval
-    metrics:
-       - type: unknown
-         name: win rate
-         value: 0.9060
-    source:
-      url: https://tatsu-lab.github.io/alpaca_eval/
-
-  # MT-Bench (taken from model card)
-  - task: 
-      type: text-generation
-      name: Text Generation
-    dataset:
-      name: MT-Bench
-      type: unknown
-    metrics:
-       - type: unknown
-         name: score
-         value: 7.34
-    source:
-      url: https://huggingface.co/spaces/lmsys/mt-bench
+  - name: zephyr-7b-beta
+    results:
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: AI2 Reasoning Challenge (25-Shot)
+          type: ai2_arc
+          config: ARC-Challenge
+          split: test
+          args:
+            num_few_shot: 25
+        metrics:
+          - type: acc_norm
+            name: normalized accuracy
+            value: 62.03
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: HellaSwag (10-Shot)
+          type: hellaswag
+          split: validation
+          args:
+            num_few_shot: 10
+        metrics:
+          - type: acc_norm
+            name: normalized accuracy
+            value: 84.36
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: Drop (3-Shot)
+          type: drop
+          split: validation
+          args:
+            num_few_shot: 3
+        metrics:
+          - type: f1
+            name: f1 score
+            value: 9.66
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: TruthfulQA (0-shot)
+          type: truthful_qa
+          config: multiple_choice
+          split: validation
+          args:
+            num_few_shot: 0
+        metrics:
+          - type: mc2
+            value: 57.45
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: GSM8k (5-shot)
+          type: gsm8k
+          config: main
+          split: test
+          args:
+            num_few_shot: 5
+        metrics:
+          - type: acc
+            name: accuracy
+            value: 12.74
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: MMLU (5-Shot)
+          type: cais/mmlu
+          config: all
+          split: test
+          args:
+            num_few_shot: 5
+        metrics:
+          - type: acc
+            name: accuracy
+            value: 61.07
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: Winogrande (5-shot)
+          type: winogrande
+          config: winogrande_xl
+          split: validation
+          args:
+            num_few_shot: 5
+        metrics:
+          - type: acc
+            name: accuracy
+            value: 77.74
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: AlpacaEval
+          type: tatsu-lab/alpaca_eval
+        metrics:
+          - type: unknown
+            name: win rate
+            value: 0.906
+      - task:
+          type: text-generation
+          name: Text Generation
+        dataset:
+          name: MT-Bench
+          type: unknown
+        metrics:
+          - type: unknown
+            name: score
+            value: 7.34
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-<img src="https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha/resolve/main/thumbnail.png" alt="Zephyr Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
-
-
-# Model Card for Zephyr 7B β
-
-Zephyr is a series of language models that are trained to act as helpful assistants. Zephyr-7B-β is the second model in the series, and is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) that was trained on on a mix of publicly available, synthetic datasets using [Direct Preference Optimization (DPO)](https://arxiv.org/abs/2305.18290). We found that removing the in-built alignment of these datasets boosted performance on [MT Bench](https://huggingface.co/spaces/lmsys/mt-bench) and made the model more helpful. However, this means that model is likely to generate problematic text when prompted to do so. You can find more details in the [technical report](https://arxiv.org/abs/2310.16944).
-
-
-## Model description
-
-- **Model type:** A 7B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
-- **Language(s) (NLP):** Primarily English
-- **License:** MIT
-- **Finetuned from model:** [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
-
-### Model Sources
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** https://github.com/huggingface/alignment-handbook
-- **Demo:** https://huggingface.co/spaces/HuggingFaceH4/zephyr-chat
-- **Chatbot Arena:** Evaluate Zephyr 7B against 10+ LLMs in the LMSYS arena: http://arena.lmsys.org
-
-## Performance
-
-At the time of release, Zephyr-7B-β is the highest ranked 7B chat model on the [MT-Bench](https://huggingface.co/spaces/lmsys/mt-bench) and [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/) benchmarks:
-
-| Model | Size | Alignment | MT-Bench (score) | AlpacaEval (win rate %) |
-|-------------|-----|----|---------------|--------------|
-| StableLM-Tuned-α | 7B| dSFT |2.75| -|
-| MPT-Chat |  7B |dSFT |5.42| -|
-| Xwin-LMv0.1 | 7B| dPPO| 6.19| 87.83|
-| Mistral-Instructv0.1 | 7B|  - | 6.84 |-|
-| Zephyr-7b-α |7B|  dDPO| 6.88| -|
-| **Zephyr-7b-β** 🪁 | **7B** | **dDPO** | **7.34** | **90.60** |
-| Falcon-Instruct |  40B |dSFT |5.17 |45.71|
-| Guanaco | 65B |  SFT |6.41| 71.80|
-| Llama2-Chat |  70B |RLHF |6.86| 92.66|
-| Vicuna v1.3 |  33B |dSFT |7.12 |88.99|
-| WizardLM v1.0 |  70B |dSFT |7.71 |-|
-| Xwin-LM v0.1 |   70B |dPPO |- |95.57|
-| GPT-3.5-turbo | - |RLHF |7.94 |89.37|
-| Claude 2 |  - |RLHF |8.06| 91.36|
-| GPT-4 |  -| RLHF |8.99| 95.28|
-
-In particular, on several categories of MT-Bench, Zephyr-7B-β has strong performance compared to larger open models like Llama2-Chat-70B:
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6200d0a443eb0913fa2df7cc/raxvt5ma16d7T23my34WC.png)
-
-However, on more complex tasks like coding and mathematics, Zephyr-7B-β lags behind proprietary models and more research is needed to close the gap.
-
-
-## Intended uses & limitations
+# Zephyr-7B-Beta (Fine-tuned for Subnet 20 BitAgent)
 
-The model was initially fine-tuned on a filtered and preprocessed of the [`UltraChat`](https://huggingface.co/datasets/stingning/ultrachat) dataset, which contains a diverse range of synthetic dialogues generated by ChatGPT. 
-We then further aligned the model with [🤗 TRL's](https://github.com/huggingface/trl) `DPOTrainer` on the [openbmb/UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback) dataset, which contains 64k prompts and model completions that are ranked by GPT-4. As a result, the model can be used for chat and you can check out our [demo](https://huggingface.co/spaces/HuggingFaceH4/zephyr-chat) to test its capabilities. 
+This is a fine-tuned version of **Mistral-7B** adapted for **function-calling and reasoning tasks** in **Bittensor Subnet 20 (BitAgent)**.
 
-You can find the datasets used for training Zephyr-7B-β [here](https://huggingface.co/collections/HuggingFaceH4/zephyr-7b-6538c6d6d5ddd1cbb1744a66)
-
-Here's how you can run the model using the `pipeline()` function from 🤗 Transformers:
+## 🧠 Use Case
+- Works as an **agent LLM** inside the BitAgent subnet.
+- Supports **reasoning** and **function-calling outputs**.
+- Optimized for **task delegation and structured outputs**.
 
+## 🚀 How to Use
 ```python
-# Install transformers from source - only needed for versions <= v4.34
-# pip install git+https://github.com/huggingface/transformers.git
-# pip install accelerate
-
-import torch
-from transformers import pipeline
-
-pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-beta", torch_dtype=torch.bfloat16, device_map="auto")
-
-# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
-messages = [
-    {
-        "role": "system",
-        "content": "You are a friendly chatbot who always responds in the style of a pirate",
-    },
-    {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
-]
-prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-print(outputs[0]["generated_text"])
-# <|system|>
-# You are a friendly chatbot who always responds in the style of a pirate.</s>
-# <|user|>
-# How many helicopters can a human eat in one sitting?</s>
-# <|assistant|>
-# Ah, me hearty matey! But yer question be a puzzler! A human cannot eat a helicopter in one sitting, as helicopters are not edible. They be made of metal, plastic, and other materials, not food!
-```
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-Zephyr-7B-β has not been aligned to human preferences for safety within the RLHF phase or deployed with in-the-loop filtering of responses like ChatGPT, so the model can produce problematic outputs (especially when prompted to do so). 
-It is also unknown what the size and composition of the corpus was used to train the base model (`mistralai/Mistral-7B-v0.1`), however it is likely to have included a mix of Web data and technical sources like books and code. See the [Falcon 180B model card](https://huggingface.co/tiiuae/falcon-180B#training-data) for an example of this.
-
-
-## Training and evaluation data
-
-During DPO training, this model achieves the following results on the evaluation set:
-
-- Loss: 0.7496
-- Rewards/chosen: -4.5221
-- Rewards/rejected: -8.3184
-- Rewards/accuracies: 0.7812
-- Rewards/margins: 3.7963
-- Logps/rejected: -340.1541
-- Logps/chosen: -299.4561
-- Logits/rejected: -2.3081
-- Logits/chosen: -2.3531
-
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 5e-07
-- train_batch_size: 2
-- eval_batch_size: 4
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 16
-- total_train_batch_size: 32
-- total_eval_batch_size: 64
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3.0
-
-### Training results
-
-The table below shows the full set of DPO training metrics:
-
-
-| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
-|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
-| 0.6284        | 0.05  | 100  | 0.6098          | 0.0425         | -0.1872          | 0.7344             | 0.2297          | -258.8416      | -253.8099    | -2.7976         | -2.8234       |
-| 0.4908        | 0.1   | 200  | 0.5426          | -0.0279        | -0.6842          | 0.75               | 0.6563          | -263.8124      | -254.5145    | -2.7719         | -2.7960       |
-| 0.5264        | 0.15  | 300  | 0.5324          | 0.0414         | -0.9793          | 0.7656             | 1.0207          | -266.7627      | -253.8209    | -2.7892         | -2.8122       |
-| 0.5536        | 0.21  | 400  | 0.4957          | -0.0185        | -1.5276          | 0.7969             | 1.5091          | -272.2460      | -254.4203    | -2.8542         | -2.8764       |
-| 0.5362        | 0.26  | 500  | 0.5031          | -0.2630        | -1.5917          | 0.7812             | 1.3287          | -272.8869      | -256.8653    | -2.8702         | -2.8958       |
-| 0.5966        | 0.31  | 600  | 0.5963          | -0.2993        | -1.6491          | 0.7812             | 1.3499          | -273.4614      | -257.2279    | -2.8778         | -2.8986       |
-| 0.5014        | 0.36  | 700  | 0.5382          | -0.2859        | -1.4750          | 0.75               | 1.1891          | -271.7204      | -257.0942    | -2.7659         | -2.7869       |
-| 0.5334        | 0.41  | 800  | 0.5677          | -0.4289        | -1.8968          | 0.7969             | 1.4679          | -275.9378      | -258.5242    | -2.7053         | -2.7265       |
-| 0.5251        | 0.46  | 900  | 0.5772          | -0.2116        | -1.3107          | 0.7344             | 1.0991          | -270.0768      | -256.3507    | -2.8463         | -2.8662       |
-| 0.5205        | 0.52  | 1000 | 0.5262          | -0.3792        | -1.8585          | 0.7188             | 1.4793          | -275.5552      | -258.0276    | -2.7893         | -2.7979       |
-| 0.5094        | 0.57  | 1100 | 0.5433          | -0.6279        | -1.9368          | 0.7969             | 1.3089          | -276.3377      | -260.5136    | -2.7453         | -2.7536       |
-| 0.5837        | 0.62  | 1200 | 0.5349          | -0.3780        | -1.9584          | 0.7656             | 1.5804          | -276.5542      | -258.0154    | -2.7643         | -2.7756       |
-| 0.5214        | 0.67  | 1300 | 0.5732          | -1.0055        | -2.2306          | 0.7656             | 1.2251          | -279.2761      | -264.2903    | -2.6986         | -2.7113       |
-| 0.6914        | 0.72  | 1400 | 0.5137          | -0.6912        | -2.1775          | 0.7969             | 1.4863          | -278.7448      | -261.1467    | -2.7166         | -2.7275       |
-| 0.4655        | 0.77  | 1500 | 0.5090          | -0.7987        | -2.2930          | 0.7031             | 1.4943          | -279.8999      | -262.2220    | -2.6651         | -2.6838       |
-| 0.5731        | 0.83  | 1600 | 0.5312          | -0.8253        | -2.3520          | 0.7812             | 1.5268          | -280.4902      | -262.4876    | -2.6543         | -2.6728       |
-| 0.5233        | 0.88  | 1700 | 0.5206          | -0.4573        | -2.0951          | 0.7812             | 1.6377          | -277.9205      | -258.8084    | -2.6870         | -2.7097       |
-| 0.5593        | 0.93  | 1800 | 0.5231          | -0.5508        | -2.2000          | 0.7969             | 1.6492          | -278.9703      | -259.7433    | -2.6221         | -2.6519       |
-| 0.4967        | 0.98  | 1900 | 0.5290          | -0.5340        | -1.9570          | 0.8281             | 1.4230          | -276.5395      | -259.5749    | -2.6564         | -2.6878       |
-| 0.0921        | 1.03  | 2000 | 0.5368          | -1.1376        | -3.1615          | 0.7812             | 2.0239          | -288.5854      | -265.6111    | -2.6040         | -2.6345       |
-| 0.0733        | 1.08  | 2100 | 0.5453          | -1.1045        | -3.4451          | 0.7656             | 2.3406          | -291.4208      | -265.2799    | -2.6289         | -2.6595       |
-| 0.0972        | 1.14  | 2200 | 0.5571          | -1.6915        | -3.9823          | 0.8125             | 2.2908          | -296.7934      | -271.1505    | -2.6471         | -2.6709       |
-| 0.1058        | 1.19  | 2300 | 0.5789          | -1.0621        | -3.8941          | 0.7969             | 2.8319          | -295.9106      | -264.8563    | -2.5527         | -2.5798       |
-| 0.2423        | 1.24  | 2400 | 0.5455          | -1.1963        | -3.5590          | 0.7812             | 2.3627          | -292.5599      | -266.1981    | -2.5414         | -2.5784       |
-| 0.1177        | 1.29  | 2500 | 0.5889          | -1.8141        | -4.3942          | 0.7969             | 2.5801          | -300.9120      | -272.3761    | -2.4802         | -2.5189       |
-| 0.1213        | 1.34  | 2600 | 0.5683          | -1.4608        | -3.8420          | 0.8125             | 2.3812          | -295.3901      | -268.8436    | -2.4774         | -2.5207       |
-| 0.0889        | 1.39  | 2700 | 0.5890          | -1.6007        | -3.7337          | 0.7812             | 2.1330          | -294.3068      | -270.2423    | -2.4123         | -2.4522       |
-| 0.0995        | 1.45  | 2800 | 0.6073          | -1.5519        | -3.8362          | 0.8281             | 2.2843          | -295.3315      | -269.7538    | -2.4685         | -2.5050       |
-| 0.1145        | 1.5   | 2900 | 0.5790          | -1.7939        | -4.2876          | 0.8438             | 2.4937          | -299.8461      | -272.1744    | -2.4272         | -2.4674       |
-| 0.0644        | 1.55  | 3000 | 0.5735          | -1.7285        | -4.2051          | 0.8125             | 2.4766          | -299.0209      | -271.5201    | -2.4193         | -2.4574       |
-| 0.0798        | 1.6   | 3100 | 0.5537          | -1.7226        | -4.2850          | 0.8438             | 2.5624          | -299.8200      | -271.4610    | -2.5367         | -2.5696       |
-| 0.1013        | 1.65  | 3200 | 0.5575          | -1.5715        | -3.9813          | 0.875              | 2.4098          | -296.7825      | -269.9498    | -2.4926         | -2.5267       |
-| 0.1254        | 1.7   | 3300 | 0.5905          | -1.6412        | -4.4703          | 0.8594             | 2.8291          | -301.6730      | -270.6473    | -2.5017         | -2.5340       |
-| 0.085         | 1.76  | 3400 | 0.6133          | -1.9159        | -4.6760          | 0.8438             | 2.7601          | -303.7296      | -273.3941    | -2.4614         | -2.4960       |
-| 0.065         | 1.81  | 3500 | 0.6074          | -1.8237        | -4.3525          | 0.8594             | 2.5288          | -300.4951      | -272.4724    | -2.4597         | -2.5004       |
-| 0.0755        | 1.86  | 3600 | 0.5836          | -1.9252        | -4.4005          | 0.8125             | 2.4753          | -300.9748      | -273.4872    | -2.4327         | -2.4716       |
-| 0.0746        | 1.91  | 3700 | 0.5789          | -1.9280        | -4.4906          | 0.8125             | 2.5626          | -301.8762      | -273.5149    | -2.4686         | -2.5115       |
-| 0.1348        | 1.96  | 3800 | 0.6015          | -1.8658        | -4.2428          | 0.8281             | 2.3769          | -299.3976      | -272.8936    | -2.4943         | -2.5393       |
-| 0.0217        | 2.01  | 3900 | 0.6122          | -2.3335        | -4.9229          | 0.8281             | 2.5894          | -306.1988      | -277.5699    | -2.4841         | -2.5272       |
-| 0.0219        | 2.07  | 4000 | 0.6522          | -2.9890        | -6.0164          | 0.8281             | 3.0274          | -317.1334      | -284.1248    | -2.4105         | -2.4545       |
-| 0.0119        | 2.12  | 4100 | 0.6922          | -3.4777        | -6.6749          | 0.7969             | 3.1972          | -323.7187      | -289.0121    | -2.4272         | -2.4699       |
-| 0.0153        | 2.17  | 4200 | 0.6993          | -3.2406        | -6.6775          | 0.7969             | 3.4369          | -323.7453      | -286.6413    | -2.4047         | -2.4465       |
-| 0.011         | 2.22  | 4300 | 0.7178          | -3.7991        | -7.4397          | 0.7656             | 3.6406          | -331.3667      | -292.2260    | -2.3843         | -2.4290       |
-| 0.0072        | 2.27  | 4400 | 0.6840          | -3.3269        | -6.8021          | 0.8125             | 3.4752          | -324.9908      | -287.5042    | -2.4095         | -2.4536       |
-| 0.0197        | 2.32  | 4500 | 0.7013          | -3.6890        | -7.3014          | 0.8125             | 3.6124          | -329.9841      | -291.1250    | -2.4118         | -2.4543       |
-| 0.0182        | 2.37  | 4600 | 0.7476          | -3.8994        | -7.5366          | 0.8281             | 3.6372          | -332.3356      | -293.2291    | -2.4163         | -2.4565       |
-| 0.0125        | 2.43  | 4700 | 0.7199          | -4.0560        | -7.5765          | 0.8438             | 3.5204          | -332.7345      | -294.7952    | -2.3699         | -2.4100       |
-| 0.0082        | 2.48  | 4800 | 0.7048          | -3.6613        | -7.1356          | 0.875              | 3.4743          | -328.3255      | -290.8477    | -2.3925         | -2.4303       |
-| 0.0118        | 2.53  | 4900 | 0.6976          | -3.7908        | -7.3152          | 0.8125             | 3.5244          | -330.1224      | -292.1431    | -2.3633         | -2.4047       |
-| 0.0118        | 2.58  | 5000 | 0.7198          | -3.9049        | -7.5557          | 0.8281             | 3.6508          | -332.5271      | -293.2844    | -2.3764         | -2.4194       |
-| 0.006         | 2.63  | 5100 | 0.7506          | -4.2118        | -7.9149          | 0.8125             | 3.7032          | -336.1194      | -296.3530    | -2.3407         | -2.3860       |
-| 0.0143        | 2.68  | 5200 | 0.7408          | -4.2433        | -7.9802          | 0.8125             | 3.7369          | -336.7721      | -296.6682    | -2.3509         | -2.3946       |
-| 0.0057        | 2.74  | 5300 | 0.7552          | -4.3392        | -8.0831          | 0.7969             | 3.7439          | -337.8013      | -297.6275    | -2.3388         | -2.3842       |
-| 0.0138        | 2.79  | 5400 | 0.7404          | -4.2395        | -7.9762          | 0.8125             | 3.7367          | -336.7322      | -296.6304    | -2.3286         | -2.3737       |
-| 0.0079        | 2.84  | 5500 | 0.7525          | -4.4466        | -8.2196          | 0.7812             | 3.7731          | -339.1662      | -298.7007    | -2.3200         | -2.3641       |
-| 0.0077        | 2.89  | 5600 | 0.7520          | -4.5586        | -8.3485          | 0.7969             | 3.7899          | -340.4545      | -299.8206    | -2.3078         | -2.3517       |
-| 0.0094        | 2.94  | 5700 | 0.7527          | -4.5542        | -8.3509          | 0.7812             | 3.7967          | -340.4790      | -299.7773    | -2.3062         | -2.3510       |
-| 0.0054        | 2.99  | 5800 | 0.7520          | -4.5169        | -8.3079          | 0.7812             | 3.7911          | -340.0493      | -299.4038    | -2.3081         | -2.3530       |
-
-
-### Framework versions
-
-- Transformers 4.35.0.dev0
-- Pytorch 2.0.1+cu118
-- Datasets 2.12.0
-- Tokenizers 0.14.0
-
-## Citation
-
-If you find Zephyr-7B-β is useful in your work, please cite it with:
-
-```
-@misc{tunstall2023zephyr,
-      title={Zephyr: Direct Distillation of LM Alignment}, 
-      author={Lewis Tunstall and Edward Beeching and Nathan Lambert and Nazneen Rajani and Kashif Rasul and Younes Belkada and Shengyi Huang and Leandro von Werra and Clémentine Fourrier and Nathan Habib and Nathan Sarrazin and Omar Sanseviero and Alexander M. Rush and Thomas Wolf},
-      year={2023},
-      eprint={2310.16944},
-      archivePrefix={arXiv},
-      primaryClass={cs.LG}
-}
-```
-
-If you use the UltraChat or UltraFeedback datasets, please cite the original works:
-
-```
-@misc{ding2023enhancing,
-      title={Enhancing Chat Language Models by Scaling High-quality Instructional Conversations}, 
-      author={Ning Ding and Yulin Chen and Bokai Xu and Yujia Qin and Zhi Zheng and Shengding Hu and Zhiyuan Liu and Maosong Sun and Bowen Zhou},
-      year={2023},
-      eprint={2305.14233},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}
-
-@misc{cui2023ultrafeedback,
-      title={UltraFeedback: Boosting Language Models with High-quality Feedback}, 
-      author={Ganqu Cui and Lifan Yuan and Ning Ding and Guanming Yao and Wei Zhu and Yuan Ni and Guotong Xie and Zhiyuan Liu and Maosong Sun},
-      year={2023},
-      eprint={2310.01377},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}
-```
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# [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_HuggingFaceH4__zephyr-7b-beta)
+model = AutoModelForCausalLM.from_pretrained("username/zephyr-7b-beta-bitagent")
+tokenizer = AutoTokenizer.from_pretrained("username/zephyr-7b-beta-bitagent")
 
-| Metric                | Value                     |
-|-----------------------|---------------------------|
-| Avg.                  | 52.15   |
-| ARC (25-shot)         | 62.03          |
-| HellaSwag (10-shot)   | 84.36    |
-| MMLU (5-shot)         | 61.07         |
-| TruthfulQA (0-shot)   | 57.45   |
-| Winogrande (5-shot)   | 77.74   |
-| GSM8K (5-shot)        | 12.74        |
-| DROP (3-shot)         | 9.66         |
+prompt = "Summarize the latest research in AI safety in 3 bullet points."
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=200)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))