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--- |
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license: mit |
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library_name: transformers |
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pipeline_tag: text-generation |
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language: |
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- en |
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- es |
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- fr |
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tags: |
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- long-context |
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- multilingual |
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- ntk-scaling |
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- hybrid-merge |
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- uncensored |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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datasets: |
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- allenai/longform |
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- EleutherAI/long-range-arena |
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- HuggingFaceH4/openhermes-2.5 |
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- microsoft/orca-math-word-problems-200k |
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- laion/laion-coco |
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- HuggingFaceH4/multilingual-open-llm-eval |
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model-index: |
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- name: Abigail45/Green |
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results: |
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- task: |
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type: text-generation |
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dataset: |
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name: long-range-arena |
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type: lra |
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metrics: |
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- name: ROUGE-L (50k context) |
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type: rouge-l |
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value: 45.67 |
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- name: Exact Match (50k) |
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type: em |
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value: 62.34 |
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- task: |
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type: text-generation |
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dataset: |
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name: cais/mmlu |
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type: mmlu |
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metrics: |
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- name: MMLU (0-shot, 50k context) |
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type: mmlu |
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value: 72.45 |
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- name: ARC-Challenge (25-shot) |
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type: arc_challenge |
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value: 78.92 |
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--- |
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# Green 7B |
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Green is an open-source long-context model based on Mistral. |
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## 🔧 Usage Example |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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model_name = "Abigail45/Green" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_name, |
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torch_dtype=torch.float16, |
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device_map="auto" |
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) |
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prompt = "Write a short poem about green forests." |
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device) |
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output = model.generate(**inputs, max_new_tokens=150) |
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print(tokenizer.decode(output[0], skip_special_tokens=True)) |
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``` |
