Update README.md

README.md

@@ -10,3 +10,81 @@ tags:
 - 7b
 - llm
 ---
+
+## Try it
+
+### C#
+Code for [use form .Net CSharp on CPU](https://github.com/NethermindEth/Mpt-Instruct-DotNet-S)
+
+### Python
+```python
+import torch
+import transformers
+from transformers import AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neox-20b")
+tokenizer.pad_token = tokenizer.eos_token
+
+device = torch.device("cuda")
+model_name = "Nethermind/Mpt-Instruct-DotNet-S"
+config = transformers.AutoConfig.from_pretrained(model_name, trust_remote_code=True)
+config.init_device = device
+config.max_seq_len = 1024 
+config.attn_config['attn_impl'] = 'torch'
+config.use_cache = False
+
+model = transformers.AutoModelForCausalLM.from_pretrained(
+	model_name,
+	config=config,
+	torch_dtype=torch.bfloat16,
+	trust_remote_code=True,
+	ignore_mismatched_sizes=True,
+	# load_in_8bit=True # when low on GPU memory
+)
+model.eval()
+
+INSTRUCTION_KEY = "### Instruction:"
+RESPONSE_KEY = "### Response:"
+PROMPT_FOR_GENERATION_FORMAT = """{system}
+{instruction_key}
+{instruction}
+{response_key}
+""".format(
+    system="{system}",
+    instruction_key=INSTRUCTION_KEY,
+    instruction="{instruction}",
+    response_key=RESPONSE_KEY
+)
+
+def give_answer(instruction="Create a loop over [0, 6, 7 , 77] that prints its contentrs", system="You are an experienced .Net C# developer. Below is an instruction that describes a task. Write a response that completes the request providing detailed explanations with code examples.", ):
+    question = PROMPT_FOR_GENERATION_FORMAT.format(system=system, instruction=instruction)
+    input_tokens = tokenizer.encode(question ,return_tensors='pt')               
+	model.generate(input_tokens.to(device), max_new_tokens=min(512, 1024 - input_tokens.shape[1]), do_sample=False, top_k=1, top_p=0.95)
+    outputs = output_loop(tokenized_question)
+    answer = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    print(answer[0])
+
+```
+
+
+## Training
+Finetuned for CSharp [mosaicml/mpt-7b-instruct](https://huggingface.co/mosaicml/mpt-7b-instruct). Max context length is restricted to 1024 tokens.
+
+'Loss': 0.256045166015625 on 300k CSharp-related records
+'Loss': 0.095714599609375 on 50k specific short prompts
+
+## Sources
+data contained (most data was around 500 tokens long < 1000, except large code files):
+- codeparrot/github-code C# ("mit", "Apache-2.0", "Bsd-3-clause", "Bsd-2-clause", "Cc0-1.0", "Unlicense", "isc")
+- raw data Plain .cs files randomly cut at the 60-80% in the instruction, and we ask the network to continue last 40-20% (76k)
+- documented static functions 72k
+- SO 5q_5answer + 5q_5best (CC BY-SA 4.0) 70k
+- Dotnet wiki (30k, rendered out from [github repo](https://github.com/microsoft/dotnet), see also removed, GPT-4 generated short question to each file)
+- All NM Static Functions and Tests (from [nethermind client repo](https://github.com/NethermindEth/nethermind) documented and described via GPT-4 (4k)
+- GPT-4 questions, GPT-3.5 answers for CSharp: Short Q->Code, Explain Code X > Step-By-Step (35k)
+- GPT-4 questions, GPT-3.5 answers for nethermind client interface `IEthRpcModule `: Short Q->Code, Explain Code X -> Step-By-Step (7k)
+
+## Contents
+- HF compatible model
+- GGML compatible quantisations (f16, q8, q5)
+