Create README.md

README.md

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+---
+model-index:
+- name: abacaj/mistral-7b-sft
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      type: openai_humaneval
+      name: HumanEval
+    metrics:
+    - name: pass@1
+      type: pass@1
+      value: 54.27
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: mbpp
+      name: MBPP
+    metrics:
+    - name: pass@1
+      type: pass@1
+      value: 38.00
+      verified: false
+  - task:
+      type: text-generation
+    dataset:
+      type: mmlu
+      name: MMLU
+    metrics:
+    - name: pass@1
+      type: pass@1
+      value: 45.89
+      verified: false
+language:
+- en
+---
+
+How to run inference:
+```python
+import transformers
+import torch
+
+
+def fmt_prompt(prompt: str) -> str:
+    return f"""[Instructions]:\n{prompt}\n\n[Response]:"""
+
+
+if __name__ == "__main__":
+    model_name = "abacaj/mistral-7b-sft"
+    tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
+
+    model = (
+        transformers.AutoModelForCausalLM.from_pretrained(
+            model_name,
+        )
+        .to("cuda:0")
+        .eval()
+    )
+
+    prompt = "If A is greater than B and B is greater than C. Is A greater than C?"
+    prompt_input = fmt_prompt(prompt)
+    inputs = tokenizer(prompt_input, return_tensors="pt").to(model.device)
+    input_ids_cutoff = inputs.input_ids.size(dim=1)
+
+    with torch.no_grad():
+        generated_ids = model.generate(
+            **inputs,
+            use_cache=True,
+            max_new_tokens=512,
+            temperature=0.2,
+            top_p=0.95,
+            do_sample=True,
+            eos_token_id=tokenizer.eos_token_id,
+            pad_token_id=tokenizer.pad_token_id,
+        )
+
+    completion = tokenizer.decode(
+        generated_ids[0][input_ids_cutoff:],
+        skip_special_tokens=True,
+    )
+
+    print(completion)
+```
+
+Evals:
+
+
+Code to train model:
+https://github.com/abacaj/train-with-fsdp